DataRobot API resources > API reference documentation > DataRobot REST API > Projects

Projects¶

This page outlines the operations, endpoints, parameters, and example requests and responses for the Projects.

GET /api/v2/deletedProjects/¶

Retrieve a list of soft-deleted projects matching search criteria

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/deletedProjects/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
searchFor	query	string	false	Project or dataset name to filter by
creator	query	string	false	Creator ID to filter projects by
organization	query	string	false	ID of organization that projects should belong to. Given project belongs to the organization the user who created the project is part of that organization.If there are no users in organization, then no projects will match the query.
deletedBefore	query	string(date-time)	false	ISO-8601 formatted date projects were deleted before
deletedAfter	query	string(date-time)	false	ISO-8601 formatted date projects were deleted after
projectId	query	string	false	Project ID to search
limit	query	integer	false	At most this many results are returned.
offset	query	integer	false	This many results will be skipped.
orderBy	query	string	false	Order deleted projects by

Enumerated Values¶

Parameter	Value
orderBy	[`projectId`, `projectName`, `datasetName`, `deletedOn`, `deletedBy`, `creator`, `-projectId`, `-projectName`, `-datasetName`, `-deletedOn`, `-deletedBy`, `-creator`]

Example responses¶

{
  "count": 0,
  "data": [
    {
      "createdBy": {
        "email": "string",
        "id": "string"
      },
      "deletedBy": {
        "email": "string",
        "id": "string"
      },
      "deletionTime": "2019-08-24T14:15:22Z",
      "fileName": "string",
      "id": "string",
      "organization": {
        "id": "string",
        "name": "string"
      },
      "projectName": "Untitled Project",
      "scheduledForDeletion": true
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	List of soft-deleted projects	DeletedProjectListResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

PATCH /api/v2/deletedProjects/{projectId}/¶

Recover (undelete) soft-deleted project

Code samples¶

# You can also use wget
curl -X PATCH https://app.datarobot.com/api/v2/deletedProjects/{projectId}/ \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter¶

{
  "action": "undelete"
}

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID.
body	body	ProjectRecover	false	none

Example responses¶

{
  "message": "string"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	Recovery operation result description	ProjectRecoverResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/deletedProjectsCount/¶

Get current number of deleted projects matching search criteria. Value is limited by DELETED_PROJECTS_BATCH_LIMIT system setting. That means that the actual amount of deleted projects can be greater than the limit, but counting will stop when reaching it.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/deletedProjectsCount/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
searchFor	query	string	false	Project or dataset name to filter by
creator	query	string	false	Creator ID to filter projects by
organization	query	string	false	ID of organization that projects should belong to. Given project belongs to the organization the user who created the project is part of that organization.If there are no users in organization, then no projects will match the query.
deletedBefore	query	string(date-time)	false	ISO-8601 formatted date projects were deleted before
deletedAfter	query	string(date-time)	false	ISO-8601 formatted date projects were deleted after
projectId	query	string	false	Project ID to search
limit	query	integer	false	Count deleted projects until specified value reached.

Example responses¶

{
  "deletedProjectsCount": 0,
  "projectCountLimit": 0,
  "valueExceedsLimit": true
}

Responses¶

Status	Meaning	Description	Schema
200	OK	Soft-deleted projects amount, current counting limit value and boolean flag to notify if an actual amount of soft-deleted projects in the system exceeds the limit value.	DeletedProjectCountResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

POST /api/v2/hdfsProjects/¶

Create a project from an HDFS file via WebHDFS API. Represent the file using URL, optionally, port, and optionally, user/password credentials. For example, {"url": "hdfs://<ip>/path/to/file.csv", "port": "50070"}.

Code samples¶

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/hdfsProjects/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{HdfsProjectCreate}'

Body parameter¶

{
  "password": "string",
  "port": 0,
  "projectName": "string",
  "url": "http://example.com",
  "user": "string"
}

Parameters

Name	In	Type	Required	Description
body	body	HdfsProjectCreate	false	none

Responses¶

Status	Meaning	Description	Schema
200	OK	none	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projectCleanupJobs/¶

Get async status of the project permadelete job

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projectCleanupJobs/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Example responses¶

{
  "jobs": [
    {
      "created": "2019-08-24T14:15:22Z",
      "data": [
        {
          "message": "string",
          "projectId": "string",
          "status": "ABORTED"
        }
      ],
      "message": "string",
      "status": "ABORTED",
      "statusId": "string"
    }
  ]
}

Responses¶

Status	Meaning	Description	Schema
200	OK	Permadelete Job Status with details per project	ProjectNukeJobListStatus

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

POST /api/v2/projectCleanupJobs/¶

Add list of projects to permadelete and returns async status

Code samples¶

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projectCleanupJobs/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{ProjectNuke}'

Body parameter¶

{
  "creator": "string",
  "deletedAfter": "2019-08-24T14:15:22Z",
  "deletedBefore": "2019-08-24T14:15:22Z",
  "limit": 1000,
  "offset": 0,
  "organization": "string",
  "projectIds": [
    "string"
  ],
  "searchFor": "string"
}

Parameters

Name	In	Type	Required	Description
body	body	ProjectNuke	false	none

Responses¶

Status	Meaning	Description	Schema
202	Accepted	Location URL to check permadelete status per project	None

Response Headers¶

Status	Header	Type	Format	Description
202	Location	string		A url that can be polled to check the status.

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

DELETE /api/v2/projectCleanupJobs/{statusId}/¶

Stop permadelete job, if possible

Code samples¶

# You can also use wget
curl -X DELETE https://app.datarobot.com/api/v2/projectCleanupJobs/{statusId}/ \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
statusId	path	string	true	The ID of the status object.

Responses¶

Status	Meaning	Description	Schema
200	OK	none	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projectCleanupJobs/{statusId}/¶

Get async status of the project permadelete job

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projectCleanupJobs/{statusId}/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
statusId	path	string	true	The ID of the status object.

Example responses¶

{
  "created": "2019-08-24T14:15:22Z",
  "data": [
    {
      "message": "string",
      "projectId": "string",
      "status": "ABORTED"
    }
  ],
  "message": "string",
  "status": "ABORTED",
  "statusId": "string"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	Permadelete Job Status with details per project	ProjectNukeJobStatus

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projectCleanupJobs/{statusId}/download/¶

Get a file containing a per-project report of permanent deletion.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projectCleanupJobs/{statusId}/download/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
statusId	path	string	true	The ID of the status object.

Example responses¶

{
  "created": "2019-08-24T14:15:22Z",
  "data": [
    {
      "message": "string",
      "projectId": "string",
      "status": "ABORTED"
    }
  ],
  "message": "string",
  "status": "ABORTED",
  "statusId": "string"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	JSON-formatted project permadeletion report.	ProjectNukeJobStatus

Response Headers¶

Status	Header	Type	Format	Description
200	Content-Disposition	string		Contains an auto generated filename for this download ('attachment;filename="project_permadeletion_.json"').

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projectCleanupJobs/{statusId}/summary/¶

Get number of projects whose deletion finished in particular state

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projectCleanupJobs/{statusId}/summary/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
statusId	path	string	true	The ID of the status object.

Example responses¶

{
  "jobId": "string",
  "summary": {
    "aborted": 0,
    "completed": 0,
    "error": 0,
    "expired": 0
  }
}

Responses¶

Status	Meaning	Description	Schema
200	OK	Project permanent deletion job status to occurrence count	ProjectNukeJobStatusSummary

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

POST /api/v2/projectClones/¶

Create a clone of an existing project.

The resultant project will begin the initial exploratory
data analysis and will be ready to set the target of the new project shortly.

Code samples¶

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projectClones/ \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{ProjectClone}'

Body parameter¶

{
  "copyOptions": false,
  "projectId": "string",
  "projectName": "string"
}

Parameters

Name	In	Type	Required	Description
body	body	ProjectClone	false	none

Example responses¶

{
  "pid": "string"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	Project cloning has successfully started. See the Location header.	ProjectCreateResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/¶

List all available projects.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
projectName	query	string	false	if provided will filter returned projects for projects with matching names
projectId	query	any	false	if provided will filter returned projects with matching project IDs
orderBy	query	string	false	if provided will order the results by this field
featureDiscovery	query	string	false	Return only feature discovery projects
offset	query	integer	false	This many results will be skipped.
limit	query	integer	false	At most this many results are returned.

Enumerated Values¶

Parameter	Value
orderBy	[`projectName`, `-projectName`]
featureDiscovery	[`false`, `False`, `true`, `True`]

Example responses¶

[
  {
    "advancedOptions": {
      "allowedPairwiseInteractionGroups": [
        [
          "string"
        ]
      ],
      "blendBestModels": true,
      "blueprintThreshold": 0,
      "considerBlendersInRecommendation": true,
      "defaultMonotonicDecreasingFeaturelistId": "string",
      "defaultMonotonicIncreasingFeaturelistId": "string",
      "downsampledMajorityRows": 0,
      "downsampledMinorityRows": 0,
      "eventsCount": "string",
      "exposure": "string",
      "majorityDownsamplingRate": 0,
      "minSecondaryValidationModelCount": true,
      "offset": [
        "string"
      ],
      "onlyIncludeMonotonicBlueprints": false,
      "prepareModelForDeployment": true,
      "responseCap": true,
      "runLeakageRemovedFeatureList": true,
      "scoringCodeOnly": true,
      "seed": "string",
      "shapOnlyMode": true,
      "smartDownsampled": true,
      "weights": "string"
    },
    "autopilotClusterList": [
      2
    ],
    "autopilotMode": 0,
    "created": "2019-08-24T14:15:22Z",
    "featureEngineeringPredictionPoint": "string",
    "fileName": "string",
    "holdoutUnlocked": true,
    "id": "string",
    "maxClusters": 2,
    "maxTrainPct": 0,
    "maxTrainRows": 0,
    "metric": "string",
    "minClusters": 2,
    "partition": {
      "cvHoldoutLevel": "string",
      "cvMethod": "random",
      "datetimeCol": "string",
      "datetimePartitionColumn": "string",
      "holdoutLevel": "string",
      "holdoutPct": 0,
      "partitionKeyCols": [
        "string"
      ],
      "reps": 0,
      "trainingLevel": "string",
      "useTimeSeries": true,
      "userPartitionCol": "string",
      "validationLevel": "string",
      "validationPct": 0,
      "validationType": "CV"
    },
    "positiveClass": 0,
    "projectName": "string",
    "stage": "string",
    "target": "string",
    "targetType": "Binary",
    "unsupervisedMode": true,
    "unsupervisedType": "anomaly",
    "useFeatureDiscovery": true
  }
]

Responses¶

Status	Meaning	Description	Schema
200	OK	The list of projects	Inline

Response Schema¶

Status Code 200

Name	Type	Required	Description
anonymous	[ProjectDetailsResponse]	false	none
» advancedOptions	ProjectAdvancedOptionsResponse	true	Information related to the current model of the deployment.
»» allowedPairwiseInteractionGroups	[array]	false	For GAM models - specify groups of columns for which pairwise interactions will be allowed. E.g. if set to [["A", "B", "C"], ["C", "D"]] then GAM models will allow interactions between columns AxB, BxC, AxC, CxD. All others (AxD, BxD) will not be considered. If not specified - all possible interactions will be considered by model.
»» blendBestModels	boolean	true	blend best models during Autopilot run [DEPRECATED]
»» blueprintThreshold	integer¦null	true	an upper bound on running time (in hours), such that models exceeding the bound will be excluded in subsequent autopilot runs
»» considerBlendersInRecommendation	boolean	false	Include blenders when selecting a model to prepare for deployment in an Autopilot Run.[DEPRECATED]
»» defaultMonotonicDecreasingFeaturelistId	string¦null	true	null or str, the ID of the featurelist specifying a set of features with a monotonically decreasing relationship to the target. All blueprints generated in the project use this as their default monotonic constraint, but it can be overriden at model submission time.
»» defaultMonotonicIncreasingFeaturelistId	string¦null	true	null or str, the ID of the featurelist specifying a set of features with a monotonically increasing relationship to the target. All blueprints generated in the project use this as their default monotonic constraint, but it can be overriden at model submission time.
»» downsampledMajorityRows	integer¦null	true	the total number of the majority rows available for modeling, or null for projects without smart downsampling
»» downsampledMinorityRows	integer¦null	true	the total number of the minority rows available for modeling, or null for projects without smart downsampling
»» eventsCount	string¦null	false	the name of the event count column, if specified, otherwise null.
»» exposure	string¦null	false	the name of the exposure column, if specified.
»» majorityDownsamplingRate	number¦null	true	the percentage between 0 and 100 of the majority rows that are kept, or null for projects without smart downsampling
»» minSecondaryValidationModelCount	boolean	false	Compute "All backtest" scores (datetime models) or cross validation scores for the specified number of highest ranking models on the Leaderboard, if over the Autopilot default.
»» offset	[string]¦null	false	the list of names of the offset columns, if specified, otherwise null.
»» onlyIncludeMonotonicBlueprints	boolean	true	whether the project only includes blueprints support enforcing monotonic constraints
»» prepareModelForDeployment	boolean¦null	true	Prepare model for deployment during Autopilot run. The preparation includes creating reduced feature list models, retraining best model on higher sample size, computing insights and assigning "RECOMMENDED FOR DEPLOYMENT" label.
»» responseCap	any	true	defaults to False, if specified used to cap the maximum response of a model

oneOf

Name	Type	Required	Restrictions	Description
»»» anonymous	boolean	false		none

xor

Name	Type	Required	Restrictions	Description
»»» anonymous	number	false	maximum: 1 minimum: 0.5	none

continued

Name	Type	Required	Restrictions	Description
»» runLeakageRemovedFeatureList	boolean	false		Run Autopilot on Leakage Removed feature list (if exists).
»» scoringCodeOnly	boolean	false		Keep only models that can be converted to scorable java code during Autopilot run.
»» seed	string¦null	true		defaults to null, the random seed to be used if specified
»» shapOnlyMode	boolean¦null	true		Keep only models that support SHAP values during Autopilot run. Use SHAP-based insights wherever possible. For pre SHAP-only mode projects this is always `null`.
»» smartDownsampled	boolean	true		whether the project uses smart downsampling to throw away excess rows of the majority class. Smart downsampled projects express all sample percents in terms of percent of minority rows (as opposed to percent of all rows).
»» weights	string¦null	true		the name of the weight column, if specified, otherwise null.
» autopilotClusterList	[integer]¦null	false	maxItems: 10	Optional. A list of integers where each value will be used as the number of clusters in Autopilot model(s) for unsupervised clustering projects. Cannot be specified unless unsupervisedMode is true and unsupervisedType is set to 'clustering'.
» autopilotMode	integer	true		The current autopilot mode, 0 for full autopilot, 2 for manual mode, 3 for quick mode, 4 for comprehensive mode
» created	string(date-time)	true		The time of project creation.
» featureEngineeringPredictionPoint	string¦null	false		The date column to be used as the prediction point for time-based feature engineering.
» fileName	string	true		The name of the dataset used to create the project.
» holdoutUnlocked	boolean	true		whether the holdout has been unlocked
» id	string	true		The ID of a project.
» maxClusters	integer¦null	false	maximum: 100 minimum: 2	Only valid when unsupervisedMode is True and unsupervisedType is 'clustering'. The maximum number of clusters allowed when training clustering models. If specified cannot be exceed the number of rows in a project's dataset divided by 50 and must be less than or equal to `minClusters`. If unsupervisedMode is True and unsupervisedType is 'clustering' then defaults to the number of rows in the project's dataset divided by 50 or 100 if that number of greater than 100.
» maxTrainPct	number	true		the maximum percentage of the dataset that can be used to successfully train a model without going into the validation data.
» maxTrainRows	integer	true		the maximum number of rows of the dataset that can be used to successfully train a model without going into the validation data
» metric	string	true		the metric used to select the best-performing models.
» minClusters	integer¦null	false	maximum: 100 minimum: 2	Only valid when unsupervisedMode is True and unsupervisedType is 'clustering'. The minimum number of clusters allowed when training clustering models. If specified cannot be exceed the number of rows in a project's dataset divided by 50 and must be less than or equal to `maxClusters`. If unsupervisedMode is True and unsupervisedType is 'clustering' then defaults to 2.
» partition	ProjectPartitionResponse	true		The partition object of a project indicates the settings used for partitioning. Depending on the partitioning selected, many of the options will be null. Note that for projects whose `cvMethod` is `"datetime"`, full specification of the partitioning method can be found at GET /api/v2/projects/{projectId}/datetimePartitioning/.
»» cvHoldoutLevel	any	true		if a user partition column was used with cross validation, the value assigned to the holdout set

anyOf

Name	Type	Required	Restrictions	Description
»»» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
»»» anonymous	number	false		none

or

Name	Type	Required	Restrictions	Description
»»» anonymous	integer	false		none

continued

Name	Type	Required	Description
»» cvMethod	string	true	the partitioning method used. Note that "date" partitioning is an old partitioning method no longer supported for new projects, as of API version v2.0.
»» datetimeCol	string¦null	true	if a date partition column was used, the name of the column. Note that datetimeCol applies to an old partitioning method no longer supported for new projects, as of API version v2.0.
»» datetimePartitionColumn	string	false	if a datetime partition column was used, the name of the column
»» holdoutLevel	any	true	if a user partition column was used with train-validation-holdout split, the value assigned to the holdout set

anyOf

Name	Type	Required	Restrictions	Description
»»» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
»»» anonymous	number	false		none

or

Name	Type	Required	Restrictions	Description
»»» anonymous	integer	false		none

continued

Name	Type	Required	Description
»» holdoutPct	number	true	the percentage of the dataset reserved for the holdout set
»» partitionKeyCols	[string]¦null	true	An array containing a single string - the name of the group partition column
»» reps	number¦null	true	if cross validation was used, the number of folds to use
»» trainingLevel	any	true	if a user partition column was used with train-validation-holdout split, the value assigned to the training set

anyOf

Name	Type	Required	Restrictions	Description
»»» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
»»» anonymous	number	false		none

or

Name	Type	Required	Restrictions	Description
»»» anonymous	integer	false		none

continued

Name	Type	Required	Description
»» useTimeSeries	boolean¦null	true	A boolean value indicating whether a time series project was created as opposed to a regular project using datetime partitioning.
»» userPartitionCol	string¦null	true	if a user partition column was used, the name of the column
»» validationLevel	any	true	if a user partition column was used with train-validation-holdout split, the value assigned to the validation set

anyOf

Name	Type	Required	Restrictions	Description
»»» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
»»» anonymous	number	false		none

or

Name	Type	Required	Restrictions	Description
»»» anonymous	integer	false		none

continued

Name	Type	Required	Description
»» validationPct	number¦null	true	if train-validation-holdout split was used, the percentage of the dataset used for the validation set
»» validationType	string	true	either CV for cross-validation or TVH for train-validation-holdout split
» positiveClass	number¦null	true	if the project uses binary classification, the class designated to be the positive class. Otherwise, null.
» projectName	string	true	The name of a project.
» stage	string	true	the stage of the project - if modeling, then the target is successfully set, and modeling or predictions can proceed.
» target	string	true	the target of the project, null if project is unsupervised.
» targetType	string¦null	true	The target type of the project.
» unsupervisedMode	boolean	true	indicates whether a project is unsupervised.
» unsupervisedType	string¦null	false	Only valid when unsupervisedMode is True. The type of unsupervised project, anomaly or clustering. If unsupervisedMode, defaults to 'anomaly'.
» useFeatureDiscovery	boolean	true	A boolean value indicating whether a feature discovery project was created as opposed to a regular project.

Enumerated Values¶

Property	Value
cvMethod	[`random`, `user`, `stratified`, `group`, `datetime`]
validationType	[`CV`, `TVH`]
targetType	[`Binary`, `Regression`, `Multiclass`, `minInflated`, `Multilabel`, `TextGeneration`, `GeoPoint`]
unsupervisedType	[`anomaly`, `clustering`]

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

POST /api/v2/projects/¶

Create a new project.

Code samples¶

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/ \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{ProjectCreate}'

Body parameter¶

{
  "credentialData": {
    "credentialType": "basic",
    "password": "string",
    "user": "string"
  },
  "credentialId": "string",
  "dataSourceId": "string",
  "datasetId": "string",
  "datasetVersionId": "string",
  "password": "string",
  "projectName": "string",
  "recipeId": "string",
  "url": "string",
  "useKerberos": true,
  "user": "string"
}

Parameters

Name	In	Type	Required	Description
body	body	ProjectCreate	false	none

Example responses¶

{
  "pid": "string"
}

Responses¶

Status	Meaning	Description	Schema
202	Accepted	Creation has successfully started. See the Location header.	ProjectCreateResponse
403	Forbidden	User does not have permission to use specified dataset item for project.	None
404	Not Found	The dataset item with the given ID or version ID is not found.	None
422	Unprocessable Entity	Ingest not yet completed.	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

DELETE /api/v2/projects/{projectId}/¶

Delete a project

Code samples¶

# You can also use wget
curl -X DELETE https://app.datarobot.com/api/v2/projects/{projectId}/ \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID.

Responses¶

Status	Meaning	Description	Schema
204	No Content	The project has been successfully deleted.	None
409	Conflict	The project is in use and cannot be deleted.	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/¶

Look up a particular project

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID.

Example responses¶

{
  "advancedOptions": {
    "allowedPairwiseInteractionGroups": [
      [
        "string"
      ]
    ],
    "blendBestModels": true,
    "blueprintThreshold": 0,
    "considerBlendersInRecommendation": true,
    "defaultMonotonicDecreasingFeaturelistId": "string",
    "defaultMonotonicIncreasingFeaturelistId": "string",
    "downsampledMajorityRows": 0,
    "downsampledMinorityRows": 0,
    "eventsCount": "string",
    "exposure": "string",
    "majorityDownsamplingRate": 0,
    "minSecondaryValidationModelCount": true,
    "offset": [
      "string"
    ],
    "onlyIncludeMonotonicBlueprints": false,
    "prepareModelForDeployment": true,
    "responseCap": true,
    "runLeakageRemovedFeatureList": true,
    "scoringCodeOnly": true,
    "seed": "string",
    "shapOnlyMode": true,
    "smartDownsampled": true,
    "weights": "string"
  },
  "autopilotClusterList": [
    2
  ],
  "autopilotMode": "0",
  "catalogId": "string",
  "catalogVersionId": "string",
  "created": "2019-08-24T14:15:22Z",
  "externalTimeSeriesBaselineDatasetMetadata": {
    "datasetId": "string",
    "datasetName": "string"
  },
  "featureEngineeringPredictionPoint": "string",
  "fileName": "string",
  "holdoutUnlocked": true,
  "id": "string",
  "isScoringAvailableForModelsTrainedIntoValidationHoldout": true,
  "maxClusters": 2,
  "maxTrainPct": 0,
  "maxTrainRows": 0,
  "metric": "string",
  "minClusters": 2,
  "partition": {
    "cvHoldoutLevel": "string",
    "cvMethod": "random",
    "datetimeCol": "string",
    "datetimePartitionColumn": "string",
    "holdoutLevel": "string",
    "holdoutPct": 0,
    "partitionKeyCols": [
      "string"
    ],
    "reps": 0,
    "trainingLevel": "string",
    "useTimeSeries": true,
    "userPartitionCol": "string",
    "validationLevel": "string",
    "validationPct": 0,
    "validationType": "CV"
  },
  "positiveClass": "string",
  "primaryLocationColumn": "string",
  "projectName": "string",
  "queryGeneratorId": "string",
  "quickrun": true,
  "relationshipsConfigurationId": "string",
  "segmentation": {
    "parentProjectId": "string",
    "segment": "string",
    "segmentationTaskId": "string"
  },
  "stage": "modeling",
  "target": "string",
  "targetType": "Binary",
  "unsupervisedMode": true,
  "unsupervisedType": "anomaly",
  "useFeatureDiscovery": true,
  "useGpu": true
}

Responses¶

Status	Meaning	Description	Schema
200	OK	The project.	ProjectRetrieveResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

PATCH /api/v2/projects/{projectId}/¶

Change project name, worker count, or unlock the holdout. If any of the optional json arguments are not provided, that aspect of the project will not be altered.

Code samples¶

# You can also use wget
curl -X PATCH https://app.datarobot.com/api/v2/projects/{projectId}/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter¶

{
  "gpuWorkerCount": 0,
  "holdoutUnlocked": "True",
  "projectDescription": "string",
  "projectName": "string",
  "workerCount": 0
}

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID.
body	body	ProjectUpdate	false	none

Responses¶

Status	Meaning	Description	Schema
200	OK	The project was successfully updated	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/accessControl/¶

Get a list of users who have access to this project and their roles on the project.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/accessControl/?offset=0&limit=0 \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
offset	query	integer	true	This many results will be skipped
limit	query	integer	true	At most this many results are returned
username	query	string	false	Optional, only return the access control information for a user with this username.
userId	query	string	false	Optional, only return the access control information for a user with this user ID.
projectId	path	string	true	The project ID

Example responses¶

{
  "count": 0,
  "data": [
    {
      "canShare": true,
      "role": "string",
      "userId": "string",
      "username": "string"
    }
  ],
  "next": "string",
  "previous": "string"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	The project's access control list.	SharingListResponse
404	Not Found	Either the project does not exist or the user does not have permissions to view the project.	None
422	Unprocessable Entity	Both username and userId were specified	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

PATCH /api/v2/projects/{projectId}/accessControl/¶

Set roles for users on this project.

Code samples¶

# You can also use wget
curl -X PATCH https://app.datarobot.com/api/v2/projects/{projectId}/accessControl/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter¶

{
  "data": [
    {
      "role": "ADMIN",
      "username": "string"
    }
  ],
  "includeFeatureDiscoveryEntities": false,
  "sendNotification": true
}

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID
body	body	SharingUpdateOrRemove	false	none

Responses¶

Status	Meaning	Description	Schema
204	No Content	Roles updated successfully.	None
409	Conflict	The request would leave the project without an owner.	None
422	Unprocessable Entity	One of the users in the request does not exist, or the request is otherwise invalid	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

PATCH /api/v2/projects/{projectId}/aim/¶

Start the data modeling process.

Code samples¶

# You can also use wget
curl -X PATCH https://app.datarobot.com/api/v2/projects/{projectId}/aim/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter¶

{
  "accuracyOptimizedMb": true,
  "aggregationType": "total",
  "allowPartialHistoryTimeSeriesPredictions": true,
  "allowedPairwiseInteractionGroups": [
    [
      "string",
      "string"
    ]
  ],
  "allowedPairwiseInteractionGroupsFilename": "string",
  "autopilotClusterList": [
    2
  ],
  "autopilotDataSamplingMethod": "random",
  "autopilotDataSelectionMethod": "duration",
  "autopilotWithFeatureDiscovery": true,
  "backtests": [
    {
      "gapDuration": "string",
      "index": 0,
      "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
      "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
      "validationDuration": "string",
      "validationEndDate": "2019-08-24T14:15:22Z",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "biasMitigationFeatureName": "string",
  "biasMitigationTechnique": "preprocessingReweighing",
  "blendBestModels": true,
  "blueprintThreshold": 1,
  "calendarId": "string",
  "chunkDefinitionId": "string",
  "classMappingAggregationSettings": {
    "aggregationClassName": "string",
    "excludedFromAggregation": [],
    "maxUnaggregatedClassValues": 1000,
    "minClassSupport": 1
  },
  "considerBlendersInRecommendation": true,
  "credentials": [
    {
      "catalogVersionId": "string",
      "password": "string",
      "url": "string",
      "user": "string"
    }
  ],
  "crossSeriesGroupByColumns": [
    "string"
  ],
  "cvHoldoutLevel": "string",
  "cvMethod": "random",
  "dateRemoval": true,
  "datetimePartitionColumn": "string",
  "datetimePartitioningId": "string",
  "defaultToAPriori": true,
  "defaultToDoNotDerive": true,
  "defaultToKnownInAdvance": true,
  "differencingMethod": "auto",
  "disableHoldout": false,
  "eventsCount": "string",
  "exponentiallyWeightedMovingAlpha": 1,
  "exposure": "string",
  "externalPredictions": [
    "string"
  ],
  "externalTimeSeriesBaselineDatasetId": "string",
  "externalTimeSeriesBaselineDatasetName": "string",
  "fairnessMetricsSet": "proportionalParity",
  "fairnessThreshold": 1,
  "featureDerivationWindowEnd": 0,
  "featureDerivationWindowStart": 0,
  "featureDiscoverySupervisedFeatureReduction": true,
  "featureEngineeringPredictionPoint": "string",
  "featureSettings": [
    {
      "aPriori": true,
      "doNotDerive": true,
      "featureName": "string",
      "knownInAdvance": true
    }
  ],
  "featurelistId": "string",
  "forecastDistance": "string",
  "forecastOffsets": [
    "string"
  ],
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "gapDuration": "string",
  "holdoutDuration": "string",
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutLevel": "string",
  "holdoutPct": 98,
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "includeBiasMitigationFeatureAsPredictorVariable": true,
  "incrementalLearningEarlyStoppingRounds": 0,
  "incrementalLearningOnBestModel": true,
  "incrementalLearningOnlyMode": true,
  "isHoldoutModified": true,
  "majorityDownsamplingRate": 0,
  "metric": "string",
  "minSecondaryValidationModelCount": 10,
  "mode": "0",
  "modelSplits": 5,
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "multiseriesIdColumns": [
    "string"
  ],
  "numberOfBacktests": 0,
  "numberOfIncrementalLearningIterationsBeforeBestModelSelection": 1,
  "offset": [
    "string"
  ],
  "onlyIncludeMonotonicBlueprints": false,
  "partitionKeyCols": [
    "string"
  ],
  "periodicities": [
    {
      "timeSteps": 0,
      "timeUnit": "MILLISECOND"
    }
  ],
  "positiveClass": "string",
  "preferableTargetValue": "string",
  "prepareModelForDeployment": true,
  "primaryLocationColumn": "string",
  "protectedFeatures": [
    "string"
  ],
  "quantileLevel": 0,
  "quickrun": true,
  "rateTopPctThreshold": 100,
  "relationshipsConfigurationId": "string",
  "reps": 2,
  "responseCap": 0.5,
  "runLeakageRemovedFeatureList": true,
  "sampleStepPct": 0,
  "scoringCodeOnly": true,
  "seed": 999999999,
  "segmentationTaskId": "string",
  "seriesId": "string",
  "shapOnlyMode": true,
  "smartDownsampled": true,
  "stopWords": [
    "string"
  ],
  "target": "string",
  "targetType": "Binary",
  "trainingLevel": "string",
  "treatAsExponential": "auto",
  "unsupervisedMode": false,
  "unsupervisedType": "anomaly",
  "useCrossSeriesFeatures": true,
  "useGpu": true,
  "useProjectSettings": true,
  "useSupervisedFeatureReduction": true,
  "useTimeSeries": false,
  "userPartitionCol": "string",
  "validationDuration": "string",
  "validationLevel": "string",
  "validationPct": 99,
  "validationType": "CV",
  "weights": "string",
  "windowsBasisUnit": "MILLISECOND"
}

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID.
body	body	Aim	false	none

Responses¶

Status	Meaning	Description	Schema
202	Accepted	Autopilot has successfully started. See the Location header.	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

POST /api/v2/projects/{projectId}/autopilot/¶

Pause or unpause the autopilot for a project.

Code samples¶

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/autopilot/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter¶

{
  "command": "start"
}

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID.
body	body	Autopilot	false	none

Responses¶

Status	Meaning	Description	Schema
202	Accepted	Request received	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

POST /api/v2/projects/{projectId}/autopilots/¶

Start autopilot on provided featurelist.

Code samples¶

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/autopilots/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter¶

{
  "autopilotClusterList": [
    2
  ],
  "blendBestModels": true,
  "considerBlendersInRecommendation": true,
  "featurelistId": "string",
  "mode": "auto",
  "prepareModelForDeployment": true,
  "runLeakageRemovedFeatureList": true,
  "scoringCodeOnly": true,
  "useGpu": true
}

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID.
body	body	AutopilotStart	false	none

Responses¶

Status	Meaning	Description	Schema
201	Created	Successfully started	None
422	Unprocessable Entity	Autopilot on this featurelist has already completed or is already in progress. This status code is also returned if target was not selected for specified project.	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/datetimePartitioning/¶

Retrieve datetime partitioning configuration

The datetime partition object in the response describes the full partitioning parameters. Since it becomes available after the target has been fully specified and the project is ready for modeling, there are some additional fields available compared to the response from POST /api/v2/projects/{projectId}/datetimePartitioning/.

The available training data corresponds to all the data available for training, while the primary training data corresponds to the data that can be used to train while ensuring that all backtests are available. If a model is trained with more data than is available in the primary training data, then all backtests may not have scores available.

All durations and datetimes will be specified in accordance with the :ref:timestamp and duration formatting rules<time_format>.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/datetimePartitioning/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID

Example responses¶

{
  "aggregationType": "total",
  "allowPartialHistoryTimeSeriesPredictions": true,
  "autopilotDataSamplingMethod": "random",
  "autopilotDataSelectionMethod": "duration",
  "availableHoldoutEndDate": "2019-08-24T14:15:22Z",
  "availableTrainingDuration": "string",
  "availableTrainingEndDate": "2019-08-24T14:15:22Z",
  "availableTrainingRowCount": 0,
  "availableTrainingStartDate": "2019-08-24T14:15:22Z",
  "backtests": [
    {
      "availableTrainingDuration": "string",
      "availableTrainingEndDate": "2019-08-24T14:15:22Z",
      "availableTrainingRowCount": 0,
      "availableTrainingStartDate": "2019-08-24T14:15:22Z",
      "gapDuration": "string",
      "gapEndDate": "2019-08-24T14:15:22Z",
      "gapRowCount": 0,
      "gapStartDate": "2019-08-24T14:15:22Z",
      "index": 0,
      "primaryTrainingDuration": "string",
      "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
      "primaryTrainingRowCount": 0,
      "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
      "totalRowCount": 0,
      "validationDuration": "string",
      "validationEndDate": "2019-08-24T14:15:22Z",
      "validationRowCount": 0,
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "calendarId": "string",
  "calendarName": "string",
  "crossSeriesGroupByColumns": [
    "string"
  ],
  "dateFormat": "string",
  "datetimePartitionColumn": "string",
  "datetimePartitioningId": "string",
  "defaultToAPriori": true,
  "defaultToDoNotDerive": true,
  "defaultToKnownInAdvance": true,
  "differencingMethod": "auto",
  "disableHoldout": true,
  "featureDerivationWindowEnd": 0,
  "featureDerivationWindowStart": 0,
  "featureSettings": [
    {
      "aPriori": true,
      "doNotDerive": true,
      "featureName": "string",
      "knownInAdvance": true
    }
  ],
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "gapDuration": "string",
  "gapEndDate": "2019-08-24T14:15:22Z",
  "gapRowCount": 0,
  "gapStartDate": "2019-08-24T14:15:22Z",
  "holdoutDuration": "string",
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutRowCount": 0,
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "isHoldoutModified": true,
  "modelSplits": 1,
  "multiseriesIdColumns": [
    "string"
  ],
  "numberOfBacktests": 1,
  "numberOfDoNotDeriveFeatures": 0,
  "numberOfKnownInAdvanceFeatures": 0,
  "partitioningExtendedWarnings": [
    {
      "backtestIndex": 0,
      "partition": "string",
      "warnings": [
        {
          "message": "string",
          "title": "string",
          "type": "string"
        }
      ]
    }
  ],
  "partitioningWarnings": [
    {
      "backtestIndex": 0,
      "partition": "string",
      "warnings": [
        "string"
      ]
    }
  ],
  "periodicities": [
    {
      "timeSteps": 0,
      "timeUnit": "MILLISECOND"
    }
  ],
  "primaryTrainingDuration": "string",
  "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
  "primaryTrainingRowCount": 0,
  "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
  "projectId": "string",
  "totalRowCount": 0,
  "treatAsExponential": "auto",
  "unsupervisedMode": true,
  "unsupervisedType": "anomaly",
  "useCrossSeriesFeatures": true,
  "useTimeSeries": true,
  "validationDuration": "string",
  "windowsBasisUnit": "MILLISECOND"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	Generated datetime partitioning.	FinalDatetimePartitioningResponse
422	Unprocessable Entity	Partitioning has not been set.	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

POST /api/v2/projects/{projectId}/datetimePartitioning/¶

Preview the fully specified datetime partitioning generated by the requested configuration. DEPRECATED: Please use the optimized partitioning route instead: POST /api/v2/projects/{projectId}/optimizedDatetimePartitionings/

Populates the full datetime partitioning that would be used if the same arguments were passed to PATCH /api/v2/projects/{projectId}/aim/ based on the requested configuration, generating defaults for all non-specified values, so that potential configurations can be tested prior to setting the target and applying a configuration.

useTimeSeries controls whether a time series project should be created or a normal project that uses datetime partitioning. See :ref:Time-Series Projects<time_series_overview> for more detail on the differences between time series projects and datetime partitioned projects. Time-series projects are only available to some users and use the additional settings of featureDerivationWindowStart and featureDerivationWindowEnd to establish feature derivation window and forecastWindowStart and forecastWindowEnd to establish a forecast window. The overview referenced above provides more information about using feature derivation and forecast windows.

When specifying a feature derivation window of a forecast window, the number of units it spans (end - start) must be an integer multiple of the timeStep of the datetimePartitionColumn.

All durations and datetimes should be specified in accordance with the :ref:timestamp and duration formatting rules<time_format>.

Code samples¶

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/datetimePartitioning/ \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter¶

{
  "aggregationType": "total",
  "allowPartialHistoryTimeSeriesPredictions": false,
  "autopilotClusterList": [
    2
  ],
  "autopilotDataSamplingMethod": "random",
  "autopilotDataSelectionMethod": "duration",
  "backtests": [
    {
      "gapDuration": "string",
      "index": 0,
      "validationDuration": "string",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "calendarId": "string",
  "clusteringBufferDisabled": false,
  "crossSeriesGroupByColumns": [
    "string"
  ],
  "datetimePartitionColumn": "string",
  "defaultToAPriori": true,
  "defaultToDoNotDerive": true,
  "defaultToKnownInAdvance": true,
  "differencingMethod": "auto",
  "disableHoldout": false,
  "featureDerivationWindowEnd": 0,
  "featureDerivationWindowStart": 0,
  "featureSettings": [
    {
      "aPriori": true,
      "doNotDerive": true,
      "featureName": "string",
      "knownInAdvance": true
    }
  ],
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "gapDuration": "string",
  "holdoutDuration": "string",
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "isHoldoutModified": true,
  "modelSplits": 5,
  "multiseriesIdColumns": [
    "string"
  ],
  "numberOfBacktests": 1,
  "periodicities": [
    {
      "timeSteps": 0,
      "timeUnit": "MILLISECOND"
    }
  ],
  "treatAsExponential": "auto",
  "unsupervisedMode": false,
  "unsupervisedType": "anomaly",
  "useCrossSeriesFeatures": false,
  "useSupervisedFeatureReduction": true,
  "useTimeSeries": false,
  "validationDuration": "string",
  "windowsBasisUnit": "MILLISECOND"
}

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID
body	body	DatetimePartitioningDataForOpenApi	false	none

Example responses¶

{
  "aggregationType": "total",
  "allowPartialHistoryTimeSeriesPredictions": true,
  "autopilotDataSamplingMethod": "random",
  "autopilotDataSelectionMethod": "duration",
  "availableHoldoutEndDate": "2019-08-24T14:15:22Z",
  "availableTrainingDuration": "string",
  "availableTrainingEndDate": "2019-08-24T14:15:22Z",
  "availableTrainingStartDate": "2019-08-24T14:15:22Z",
  "backtests": [
    {
      "availableTrainingDuration": "string",
      "availableTrainingEndDate": "2019-08-24T14:15:22Z",
      "availableTrainingStartDate": "2019-08-24T14:15:22Z",
      "gapDuration": "string",
      "gapEndDate": "2019-08-24T14:15:22Z",
      "gapStartDate": "2019-08-24T14:15:22Z",
      "index": 0,
      "primaryTrainingDuration": "string",
      "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
      "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
      "validationDuration": "string",
      "validationEndDate": "2019-08-24T14:15:22Z",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "calendarId": "string",
  "calendarName": "string",
  "clusteringBufferDisabled": false,
  "crossSeriesGroupByColumns": [
    "string"
  ],
  "dateFormat": "string",
  "datetimePartitionColumn": "string",
  "datetimePartitioningId": "string",
  "defaultToAPriori": true,
  "defaultToDoNotDerive": true,
  "defaultToKnownInAdvance": true,
  "differencingMethod": "auto",
  "disableHoldout": true,
  "featureDerivationWindowEnd": 0,
  "featureDerivationWindowStart": 0,
  "featureSettings": [
    {
      "aPriori": true,
      "doNotDerive": true,
      "featureName": "string",
      "knownInAdvance": true
    }
  ],
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "gapDuration": "string",
  "gapEndDate": "2019-08-24T14:15:22Z",
  "gapStartDate": "2019-08-24T14:15:22Z",
  "holdoutDuration": "string",
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "isHoldoutModified": true,
  "modelSplits": 1,
  "multiseriesIdColumns": [
    "string"
  ],
  "numberOfBacktests": 1,
  "numberOfDoNotDeriveFeatures": 0,
  "numberOfKnownInAdvanceFeatures": 0,
  "partitioningExtendedWarnings": [
    {
      "backtestIndex": 0,
      "partition": "string",
      "warnings": [
        {
          "message": "string",
          "title": "string",
          "type": "string"
        }
      ]
    }
  ],
  "partitioningWarnings": [
    {
      "backtestIndex": 0,
      "partition": "string",
      "warnings": [
        "string"
      ]
    }
  ],
  "periodicities": [
    {
      "timeSteps": 0,
      "timeUnit": "MILLISECOND"
    }
  ],
  "primaryTrainingDuration": "string",
  "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
  "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
  "projectId": "string",
  "treatAsExponential": "auto",
  "unsupervisedMode": true,
  "unsupervisedType": "anomaly",
  "useCrossSeriesFeatures": true,
  "useTimeSeries": true,
  "validationDuration": "string",
  "windowsBasisUnit": "MILLISECOND"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	Generated datetime partitioning.	DatetimePartitioningResponse
404	Not Found	Requested feature was not found.	None
422	Unprocessable Entity	Partitioning generation failed.	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

POST /api/v2/projects/{projectId}/externalTimeSeriesBaselineDataValidationJobs/¶

This route validates if a provided catalog version id can be used as baseline for calculating metrics. This functionality is available only for time series projects.For a baseline dataset to be valid, the number of unique date amd multiseries_id columnrows must match the unique number of date and multiseries_id column rows in the uploadedtraining dataset. This functionality is limited to one forecast distance. Additionally, the catalog must be a snapshot.

Code samples¶

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/externalTimeSeriesBaselineDataValidationJobs/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter¶

{
  "backtests": [
    {
      "validationEndDate": "2019-08-24T14:15:22Z",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "catalogVersionId": "string",
  "datetimePartitionColumn": "string",
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "multiseriesIdColumns": [
    "string"
  ],
  "target": "string"
}

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID
body	body	ExternalTSBaselinePayload	false	none

Responses¶

Status	Meaning	Description	Schema
202	Accepted	Validate baseline data that is provided in the form of a catalog version id. We willconfirm that the dataset contains the proper date, target column, and multiseries ID column. If the provided dataset meets the criteria, the job will be successful.	None
403	Forbidden	User does not have access to this functionality.	None
422	Unprocessable Entity	Unable to process external time sereis baseline validation job.	None

Response Headers¶

Status	Header	Type	Format	Description
202	Location	string		A url that can be polled to check the status.

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/externalTimeSeriesBaselineDataValidationJobs/{baselineValidationJobId}/¶

Retrieve information to confirm if the validation job triggered via /api/v2/projects/(projectId)/externalTimeSeriesBaselineDataValidationJobs/ is valid.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/externalTimeSeriesBaselineDataValidationJobs/{baselineValidationJobId}/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project to retrieve the validation job information from.
baselineValidationJobId	path	string	true	The id for the validation job

Example responses¶

{
  "backtests": [
    {
      "validationEndDate": "2019-08-24T14:15:22Z",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "baselineValidationJobId": "string",
  "catalogVersionId": "string",
  "datetimePartitionColumn": "string",
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "isExternalBaselineDatasetValid": true,
  "message": "string",
  "multiseriesIdColumns": [
    "string"
  ],
  "projectId": "string",
  "target": "string"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	none	ExternalTSBaselineResponse
403	Forbidden	User does not have access to this functionality.	None
404	Not Found	External time series validation job not found.	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/jobs/¶

List the project's jobs.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/jobs/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
status	query	string	false	If provided, only jobs with the same status will be included in the results; otherwise, queued and inprogress jobs (but not errored jobs) will be returned.
projectId	path	string	true	The project ID.

Enumerated Values¶

Parameter	Value
status	[`queue`, `inprogress`, `error`]

Example responses¶

{
  "count": 0,
  "jobs": [
    {
      "id": "string",
      "isBlocked": true,
      "jobType": "model",
      "message": "string",
      "modelId": "string",
      "projectId": "string",
      "status": "queue",
      "url": "string"
    }
  ],
  "next": "string",
  "previous": "string"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	The project's jobs	JobListResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

DELETE /api/v2/projects/{projectId}/jobs/{jobId}/¶

Cancel a pending job.

Code samples¶

# You can also use wget
curl -X DELETE https://app.datarobot.com/api/v2/projects/{projectId}/jobs/{jobId}/ \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID.
jobId	path	string	true	The job ID

Responses¶

Status	Meaning	Description	Schema
204	No Content	The job has been canceled.	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/jobs/{jobId}/¶

Retrieve details for a job that has been started but has not yet completed.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/jobs/{jobId}/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID.
jobId	path	string	true	The job ID

Example responses¶

{
  "id": "string",
  "isBlocked": true,
  "jobType": "model",
  "message": "string",
  "modelId": "string",
  "projectId": "string",
  "status": "queue",
  "url": "string"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	The job details	JobDetailsResponse
303	See Other	The requested job has already finished. See the Location header for the job details.	None

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/multiseriesIds/{multiseriesId}/crossSeriesProperties/¶

Retrieve eligible cross-series group-by columns.

Note that validation will have to have been triggered via [POST /api/v2/projects/{projectId}/crossSeriesProperties/][post-apiv2projectsprojectidcrossseriesproperties] in order for results to appear here.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/multiseriesIds/{multiseriesId}/crossSeriesProperties/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
crossSeriesGroupByColumns	query	any	false	The names of the columns to retrieve the validation status for. If not specified, all eligible columns will be returned.
projectId	path	string	true	The project to retrieve cross-series group-by columns for.
multiseriesId	path	string	true	The name of the column to be used as the multiseries ID column.

Example responses¶

{
  "crossSeriesGroupByColumns": [
    {
      "eligibility": "string",
      "isEligible": true,
      "name": "string"
    }
  ],
  "multiseriesId": "string"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	Request was successful.	CrossSeriesGroupByColumnRetrieveResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/multiseriesNames/¶

List the individual series names of a multiseries project

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/multiseriesNames/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
offset	query	integer	false	Number of results to skip.
limit	query	integer	false	At most this many results are returned. The default may change without notice.
projectId	path	string	true	The project ID

Example responses¶

{
  "count": 0,
  "data": {
    "items": [
      "string"
    ]
  },
  "next": "string",
  "previous": "string",
  "totalSeriesCount": 0
}

Responses¶

Status	Meaning	Description	Schema
200	OK	none	MultiseriesNamesControllerResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

POST /api/v2/projects/{projectId}/multiseriesProperties/¶

Analyze relationships between potential partition and multiseries ID columns. Time series projects require that each timestamp have at most one row corresponding to it. However, multiple series of data can be handled within a single project by designating a multiseries ID column that assigns each row to a particular series. See the :ref:multiseries <multiseries> docs on time series projects for more information. A detection job analyzing the relationship between the multiseries ID column and the datetime partition column must be ran before it can be used. If the desired multiseries ID column(s) are known, it can be specified to limit the analysis to only those columns.

Code samples¶

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/multiseriesProperties/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter¶

{
  "datetimePartitionColumn": "string",
  "multiseriesIdColumns": [
    "string"
  ]
}

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID
body	body	MultiseriesPayload	false	none

Responses¶

Status	Meaning	Description	Schema
202	Accepted	Request to analyze relationships between potential partition and multiseries ID columns was submitted. See Location header.	None

Response Headers¶

Status	Header	Type	Format	Description
202	Location	string		A url that can be polled to check the status.

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/optimizedDatetimePartitionings/¶

List all created optimized datetime partitioning configurations

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/optimizedDatetimePartitionings/?limit=10 \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
offset	query	integer	false	This many results will be skipped.
limit	query	integer	true	At most this many results are returned.
projectId	path	string	true	The project ID

Example responses¶

{
  "count": 0,
  "data": [
    {
      "datetimePartitionColumn": "string",
      "id": "string",
      "partitionData": {
        "aggregationType": "total",
        "allowPartialHistoryTimeSeriesPredictions": true,
        "autopilotDataSamplingMethod": "random",
        "autopilotDataSelectionMethod": "duration",
        "availableHoldoutEndDate": "2019-08-24T14:15:22Z",
        "availableTrainingDuration": "string",
        "availableTrainingEndDate": "2019-08-24T14:15:22Z",
        "availableTrainingStartDate": "2019-08-24T14:15:22Z",
        "backtests": [
          {
            "availableTrainingDuration": "string",
            "availableTrainingEndDate": "2019-08-24T14:15:22Z",
            "availableTrainingStartDate": "2019-08-24T14:15:22Z",
            "gapDuration": "string",
            "gapEndDate": "2019-08-24T14:15:22Z",
            "gapStartDate": "2019-08-24T14:15:22Z",
            "index": 0,
            "primaryTrainingDuration": "string",
            "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
            "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
            "validationDuration": "string",
            "validationEndDate": "2019-08-24T14:15:22Z",
            "validationStartDate": "2019-08-24T14:15:22Z"
          }
        ],
        "calendarId": "string",
        "calendarName": "string",
        "clusteringBufferDisabled": false,
        "crossSeriesGroupByColumns": [
          "string"
        ],
        "dateFormat": "string",
        "datetimePartitionColumn": "string",
        "datetimePartitioningId": "string",
        "defaultToAPriori": true,
        "defaultToDoNotDerive": true,
        "defaultToKnownInAdvance": true,
        "differencingMethod": "auto",
        "disableHoldout": true,
        "featureDerivationWindowEnd": 0,
        "featureDerivationWindowStart": 0,
        "featureSettings": [
          {
            "aPriori": true,
            "doNotDerive": true,
            "featureName": "string",
            "knownInAdvance": true
          }
        ],
        "forecastWindowEnd": 0,
        "forecastWindowStart": 0,
        "gapDuration": "string",
        "gapEndDate": "2019-08-24T14:15:22Z",
        "gapStartDate": "2019-08-24T14:15:22Z",
        "holdoutDuration": "string",
        "holdoutEndDate": "2019-08-24T14:15:22Z",
        "holdoutStartDate": "2019-08-24T14:15:22Z",
        "isHoldoutModified": true,
        "modelSplits": 1,
        "multiseriesIdColumns": [
          "string"
        ],
        "numberOfBacktests": 1,
        "numberOfDoNotDeriveFeatures": 0,
        "numberOfKnownInAdvanceFeatures": 0,
        "partitioningExtendedWarnings": [
          {
            "backtestIndex": 0,
            "partition": "string",
            "warnings": [
              {
                "message": "string",
                "title": "string",
                "type": "string"
              }
            ]
          }
        ],
        "partitioningWarnings": [
          {
            "backtestIndex": 0,
            "partition": "string",
            "warnings": [
              "string"
            ]
          }
        ],
        "periodicities": [
          {
            "timeSteps": 0,
            "timeUnit": "MILLISECOND"
          }
        ],
        "primaryTrainingDuration": "string",
        "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
        "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
        "projectId": "string",
        "treatAsExponential": "auto",
        "unsupervisedMode": true,
        "unsupervisedType": "anomaly",
        "useCrossSeriesFeatures": true,
        "useTimeSeries": true,
        "validationDuration": "string",
        "windowsBasisUnit": "MILLISECOND"
      },
      "target": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	List of optimized datetime partitionings for projectId	OptimizedDatetimePartitioningListResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

POST /api/v2/projects/{projectId}/optimizedDatetimePartitionings/¶

Create an optimized datetime partitioning configuration using the target.

Initializes a job to construct an optimized datetime partitioning using the date and target information to ensure that backtests sufficiently cover regions of interest in the target. This is an asynchronous job. The results of the asynchronous job (backtests and other parameters can be used in the synchronous version.

useTimeSeries controls whether a time series project should be created or a normal project that uses datetime partitioning. See :ref:Time-Series Projects<time_series_overview> for more detail on the differences between time series projects and datetime partitioned projects. Time-series projects are only available to some users and use the additional settings of featureDerivationWindowStart and featureDerivationWindowEnd to establish feature derivation window and forecastWindowStart and forecastWindowEnd to establish a forecast window. The overview referenced above provides more information about using feature derivation and forecast windows.

When specifying a feature derivation window of a forecast window, the number of units it spans (end - start) must be an integer multiple of the timeStep of the datetimePartitionColumn.

All durations and datetimes should be specified in accordance with the :ref:timestamp and duration formatting rules<time_format>.

Code samples¶

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/optimizedDatetimePartitionings/ \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter¶

{
  "aggregationType": "total",
  "allowPartialHistoryTimeSeriesPredictions": false,
  "autopilotClusterList": [
    2
  ],
  "autopilotDataSamplingMethod": "random",
  "autopilotDataSelectionMethod": "duration",
  "backtests": [
    {
      "gapDuration": "string",
      "index": 0,
      "validationDuration": "string",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "calendarId": "string",
  "clusteringBufferDisabled": false,
  "crossSeriesGroupByColumns": [
    "string"
  ],
  "datetimePartitionColumn": "string",
  "defaultToAPriori": true,
  "defaultToDoNotDerive": true,
  "defaultToKnownInAdvance": true,
  "differencingMethod": "auto",
  "disableHoldout": false,
  "featureDerivationWindowEnd": 0,
  "featureDerivationWindowStart": 0,
  "featureSettings": [
    {
      "aPriori": true,
      "doNotDerive": true,
      "featureName": "string",
      "knownInAdvance": true
    }
  ],
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "gapDuration": "string",
  "holdoutDuration": "string",
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "isHoldoutModified": true,
  "modelSplits": 5,
  "multiseriesIdColumns": [
    "string"
  ],
  "numberOfBacktests": 1,
  "periodicities": [
    {
      "timeSteps": 0,
      "timeUnit": "MILLISECOND"
    }
  ],
  "target": "string",
  "treatAsExponential": "auto",
  "unsupervisedMode": false,
  "unsupervisedType": "anomaly",
  "useCrossSeriesFeatures": false,
  "useSupervisedFeatureReduction": true,
  "useTimeSeries": false,
  "validationDuration": "string",
  "windowsBasisUnit": "MILLISECOND"
}

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID
body	body	OptimizedDatetimePartitioningData	false	none

Example responses¶

{
  "aggregationType": "total",
  "allowPartialHistoryTimeSeriesPredictions": true,
  "autopilotDataSamplingMethod": "random",
  "autopilotDataSelectionMethod": "duration",
  "availableHoldoutEndDate": "2019-08-24T14:15:22Z",
  "availableTrainingDuration": "string",
  "availableTrainingEndDate": "2019-08-24T14:15:22Z",
  "availableTrainingStartDate": "2019-08-24T14:15:22Z",
  "backtests": [
    {
      "availableTrainingDuration": "string",
      "availableTrainingEndDate": "2019-08-24T14:15:22Z",
      "availableTrainingStartDate": "2019-08-24T14:15:22Z",
      "gapDuration": "string",
      "gapEndDate": "2019-08-24T14:15:22Z",
      "gapStartDate": "2019-08-24T14:15:22Z",
      "index": 0,
      "primaryTrainingDuration": "string",
      "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
      "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
      "validationDuration": "string",
      "validationEndDate": "2019-08-24T14:15:22Z",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "calendarId": "string",
  "calendarName": "string",
  "clusteringBufferDisabled": false,
  "crossSeriesGroupByColumns": [
    "string"
  ],
  "dateFormat": "string",
  "datetimePartitionColumn": "string",
  "datetimePartitioningId": "string",
  "defaultToAPriori": true,
  "defaultToDoNotDerive": true,
  "defaultToKnownInAdvance": true,
  "differencingMethod": "auto",
  "disableHoldout": true,
  "featureDerivationWindowEnd": 0,
  "featureDerivationWindowStart": 0,
  "featureSettings": [
    {
      "aPriori": true,
      "doNotDerive": true,
      "featureName": "string",
      "knownInAdvance": true
    }
  ],
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "gapDuration": "string",
  "gapEndDate": "2019-08-24T14:15:22Z",
  "gapStartDate": "2019-08-24T14:15:22Z",
  "holdoutDuration": "string",
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "isHoldoutModified": true,
  "modelSplits": 1,
  "multiseriesIdColumns": [
    "string"
  ],
  "numberOfBacktests": 1,
  "numberOfDoNotDeriveFeatures": 0,
  "numberOfKnownInAdvanceFeatures": 0,
  "partitioningExtendedWarnings": [
    {
      "backtestIndex": 0,
      "partition": "string",
      "warnings": [
        {
          "message": "string",
          "title": "string",
          "type": "string"
        }
      ]
    }
  ],
  "partitioningWarnings": [
    {
      "backtestIndex": 0,
      "partition": "string",
      "warnings": [
        "string"
      ]
    }
  ],
  "periodicities": [
    {
      "timeSteps": 0,
      "timeUnit": "MILLISECOND"
    }
  ],
  "primaryTrainingDuration": "string",
  "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
  "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
  "projectId": "string",
  "treatAsExponential": "auto",
  "unsupervisedMode": true,
  "unsupervisedType": "anomaly",
  "useCrossSeriesFeatures": true,
  "useTimeSeries": true,
  "validationDuration": "string",
  "windowsBasisUnit": "MILLISECOND"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	Generated datetime partitioning.	DatetimePartitioningResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/optimizedDatetimePartitionings/{datetimePartitioningId}/¶

Retrieve optimized datetime partitioning configuration

The optimized datetime partition objects are structurally identical to the original datetime partition objects, however they are retrieved from a mongo database after creation as opposed to being calculated synchronously. The datetime partition object in the response describes the full partitioning parameters.

The available training data corresponds to all the data available for training, while the primary training data corresponds to the data that can be used to train while ensuring that all backtests are available. If a model is trained with more data than is available in the primary training data, then all backtests may not have scores available.

.. note:: All durations and datetimes should be specified in accordance with the :ref:timestamp and duration formatting rules <time_format>.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/optimizedDatetimePartitionings/{datetimePartitioningId}/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID
datetimePartitioningId	path	string	true	The ID of the datetime partitioning to retrieve.

Example responses¶

{
  "aggregationType": "total",
  "allowPartialHistoryTimeSeriesPredictions": true,
  "autopilotDataSamplingMethod": "random",
  "autopilotDataSelectionMethod": "duration",
  "availableHoldoutEndDate": "2019-08-24T14:15:22Z",
  "availableTrainingDuration": "string",
  "availableTrainingEndDate": "2019-08-24T14:15:22Z",
  "availableTrainingStartDate": "2019-08-24T14:15:22Z",
  "backtests": [
    {
      "availableTrainingDuration": "string",
      "availableTrainingEndDate": "2019-08-24T14:15:22Z",
      "availableTrainingStartDate": "2019-08-24T14:15:22Z",
      "gapDuration": "string",
      "gapEndDate": "2019-08-24T14:15:22Z",
      "gapStartDate": "2019-08-24T14:15:22Z",
      "index": 0,
      "primaryTrainingDuration": "string",
      "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
      "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
      "validationDuration": "string",
      "validationEndDate": "2019-08-24T14:15:22Z",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "calendarId": "string",
  "calendarName": "string",
  "clusteringBufferDisabled": false,
  "crossSeriesGroupByColumns": [
    "string"
  ],
  "dateFormat": "string",
  "datetimePartitionColumn": "string",
  "datetimePartitioningId": "string",
  "defaultToAPriori": true,
  "defaultToDoNotDerive": true,
  "defaultToKnownInAdvance": true,
  "differencingMethod": "auto",
  "disableHoldout": true,
  "featureDerivationWindowEnd": 0,
  "featureDerivationWindowStart": 0,
  "featureSettings": [
    {
      "aPriori": true,
      "doNotDerive": true,
      "featureName": "string",
      "knownInAdvance": true
    }
  ],
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "gapDuration": "string",
  "gapEndDate": "2019-08-24T14:15:22Z",
  "gapStartDate": "2019-08-24T14:15:22Z",
  "holdoutDuration": "string",
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "isHoldoutModified": true,
  "modelSplits": 1,
  "multiseriesIdColumns": [
    "string"
  ],
  "numberOfBacktests": 1,
  "numberOfDoNotDeriveFeatures": 0,
  "numberOfKnownInAdvanceFeatures": 0,
  "partitioningExtendedWarnings": [
    {
      "backtestIndex": 0,
      "partition": "string",
      "warnings": [
        {
          "message": "string",
          "title": "string",
          "type": "string"
        }
      ]
    }
  ],
  "partitioningWarnings": [
    {
      "backtestIndex": 0,
      "partition": "string",
      "warnings": [
        "string"
      ]
    }
  ],
  "periodicities": [
    {
      "timeSteps": 0,
      "timeUnit": "MILLISECOND"
    }
  ],
  "primaryTrainingDuration": "string",
  "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
  "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
  "projectId": "string",
  "treatAsExponential": "auto",
  "unsupervisedMode": true,
  "unsupervisedType": "anomaly",
  "useCrossSeriesFeatures": true,
  "useTimeSeries": true,
  "validationDuration": "string",
  "windowsBasisUnit": "MILLISECOND"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	Optimized datetime partitioning configuration	DatetimePartitioningResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/optimizedDatetimePartitionings/{datetimePartitioningId}/datetimePartitioningInput/¶

Retrieve optimized datetime partitioning input

The datetime partition object in the response describes the inputs used to create the full partitioning object.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/optimizedDatetimePartitionings/{datetimePartitioningId}/datetimePartitioningInput/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID
datetimePartitioningId	path	string	true	The ID of the datetime partitioning to retrieve.

Example responses¶

{
  "aggregationType": "total",
  "allowPartialHistoryTimeSeriesPredictions": false,
  "autopilotClusterList": [
    2
  ],
  "autopilotDataSamplingMethod": "random",
  "autopilotDataSelectionMethod": "duration",
  "backtests": [
    {
      "gapDuration": "string",
      "index": 0,
      "validationDuration": "string",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "calendarId": "string",
  "clusteringBufferDisabled": false,
  "crossSeriesGroupByColumns": [
    "string"
  ],
  "datetimePartitionColumn": "string",
  "defaultToAPriori": true,
  "defaultToDoNotDerive": true,
  "defaultToKnownInAdvance": true,
  "differencingMethod": "auto",
  "disableHoldout": false,
  "featureDerivationWindowEnd": 0,
  "featureDerivationWindowStart": 0,
  "featureSettings": [
    {
      "aPriori": true,
      "doNotDerive": true,
      "featureName": "string",
      "knownInAdvance": true
    }
  ],
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "gapDuration": "string",
  "holdoutDuration": "string",
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "isHoldoutModified": true,
  "modelSplits": 5,
  "multiseriesIdColumns": [
    "string"
  ],
  "numberOfBacktests": 1,
  "periodicities": [
    {
      "timeSteps": 0,
      "timeUnit": "MILLISECOND"
    }
  ],
  "target": "string",
  "treatAsExponential": "auto",
  "unsupervisedMode": false,
  "unsupervisedType": "anomaly",
  "useCrossSeriesFeatures": false,
  "useSupervisedFeatureReduction": true,
  "useTimeSeries": false,
  "validationDuration": "string",
  "windowsBasisUnit": "MILLISECOND"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	Optimized datetime partitioning input	OptimizedDatetimePartitioningData

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/optimizedDatetimePartitionings/{datetimePartitioningId}/datetimePartitioningLog/¶

Retrieve the datetime partitioning log content and log length for an optimized datetime partitioning as JSON.

The Date/Time Partitioning Log provides details about the partitioning process for an OTV or Time Series project.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/optimizedDatetimePartitionings/{datetimePartitioningId}/datetimePartitioningLog/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
offset	query	integer	false	Number of results to skip.
limit	query	integer	false	At most this many results are returned. The default may change without notice.
projectId	path	string	true	The project ID
datetimePartitioningId	path	string	true	The ID of the datetime partitioning to retrieve.

Example responses¶

{
  "count": 0,
  "datetimePartitioningLog": "string",
  "next": "http://example.com",
  "previous": "http://example.com",
  "totalLogLines": 0
}

Responses¶

Status	Meaning	Description	Schema
200	OK	none	DatetimePartitioningLogListControllerResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/optimizedDatetimePartitionings/{datetimePartitioningId}/datetimePartitioningLog/file/¶

Retrieve a text file containing the datetime partitioning log.

The Date/Time Partitioning Log provides details about the partitioning process for an OTV or Time Series project.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/optimizedDatetimePartitionings/{datetimePartitioningId}/datetimePartitioningLog/file/ \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID
datetimePartitioningId	path	string	true	The ID of the datetime partitioning to retrieve.

Responses¶

Status	Meaning	Description	Schema
200	OK	none	None

Response Headers¶

Status	Header	Type	Format	Description
200	Content-Disposition	string		`attachment;filename=<filename>.txt` The suggested filename is dynamically generated
200	Content-Type	string		MIME type of the returned data

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/segmentationTaskJobResults/{segmentationTaskId}/¶

Retrieve the statuses of segmentation task jobs associated with the ID.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/segmentationTaskJobResults/{segmentationTaskId}/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID
segmentationTaskId	path	string	true	The ID of the segmentation task to check the status of.

Example responses¶

{
  "completedJobs": [
    {
      "name": "string",
      "segmentationTaskId": "string",
      "segmentsCount": 0,
      "segmentsEda": [
        {
          "maxDate": "2019-08-24T14:15:22Z",
          "minDate": "2019-08-24T14:15:22Z",
          "name": "string",
          "numberOfRows": 0,
          "sizeInBytes": 0
        }
      ],
      "url": "string"
    }
  ],
  "failedJobs": [
    {
      "message": "string",
      "name": "string",
      "parameters": {}
    }
  ],
  "numberOfJobs": 0
}

Responses¶

Status	Meaning	Description	Schema
200	OK	none	SegmentationResultsResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/segmentationTasks/¶

List all segmentation tasks created for the project.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/segmentationTasks/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
offset	query	integer	false	This many results will be skipped.
limit	query	integer	false	At most this many results are returned.
projectId	path	string	true	The project ID

Example responses¶

{
  "count": 0,
  "data": [
    {
      "created": "2019-08-24T14:15:22Z",
      "data": {
        "clusteringModelId": "string",
        "clusteringModelName": "string",
        "clusteringProjectId": "string",
        "datetimePartitionColumn": "string",
        "modelPackageId": "string",
        "multiseriesIdColumns": [
          "string"
        ],
        "userDefinedSegmentIdColumns": [
          "string"
        ]
      },
      "metadata": {
        "useAutomatedSegmentation": true,
        "useMultiseriesIdColumns": true,
        "useTimeSeries": true
      },
      "name": "string",
      "projectId": "string",
      "segmentationTaskId": "string",
      "segments": [
        "string"
      ],
      "segmentsCount": 0,
      "segmentsEda": [
        {
          "maxDate": "2019-08-24T14:15:22Z",
          "minDate": "2019-08-24T14:15:22Z",
          "name": "string",
          "numberOfRows": 0,
          "sizeInBytes": 0
        }
      ],
      "type": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	none	SegmentationTaskListResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

POST /api/v2/projects/{projectId}/segmentationTasks/¶

Create segmentation tasks for the dataset used in the project.

Code samples¶

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/projects/{projectId}/segmentationTasks/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter¶

{
  "datetimePartitionColumn": "string",
  "modelPackageId": "string",
  "multiseriesIdColumns": [
    "string"
  ],
  "target": "string",
  "useAutomatedSegmentation": false,
  "useTimeSeries": false,
  "userDefinedSegmentIdColumns": [
    "string"
  ]
}

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID
body	body	SegmentationTaskCreate	false	none

Responses¶

Status	Meaning	Description	Schema
202	Accepted	Job submitted. See Location header.	None

Response Headers¶

Status	Header	Type	Format	Description
202	Location	string		A url that can be polled to check the status.

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/segmentationTasks/{segmentationTaskId}/¶

Retrieve information about a segmentation task.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/segmentationTasks/{segmentationTaskId}/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID
segmentationTaskId	path	string	true	The ID of the segmentation task.

Example responses¶

{
  "created": "2019-08-24T14:15:22Z",
  "data": {
    "clusteringModelId": "string",
    "clusteringModelName": "string",
    "clusteringProjectId": "string",
    "datetimePartitionColumn": "string",
    "modelPackageId": "string",
    "multiseriesIdColumns": [
      "string"
    ],
    "userDefinedSegmentIdColumns": [
      "string"
    ]
  },
  "metadata": {
    "useAutomatedSegmentation": true,
    "useMultiseriesIdColumns": true,
    "useTimeSeries": true
  },
  "name": "string",
  "projectId": "string",
  "segmentationTaskId": "string",
  "segments": [
    "string"
  ],
  "segmentsCount": 0,
  "segmentsEda": [
    {
      "maxDate": "2019-08-24T14:15:22Z",
      "minDate": "2019-08-24T14:15:22Z",
      "name": "string",
      "numberOfRows": 0,
      "sizeInBytes": 0
    }
  ],
  "type": "string"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	none	SegmentationTaskResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/segmentationTasks/{segmentationTaskId}/mappings/¶

Retrieve the seriesId to segmentId mappings for a Segmentation Task.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/segmentationTasks/{segmentationTaskId}/mappings/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
offset	query	integer	false	This many results will be skipped.
limit	query	integer	false	At most this many results are returned.
projectId	path	string	true	The project ID
segmentationTaskId	path	string	true	The ID of the segmentation task.

Example responses¶

{
  "count": 0,
  "data": [
    {
      "segment": "string",
      "seriesId": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	none	SegmentationTaskSegmentMappingsResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

PATCH /api/v2/projects/{projectId}/segments/{segmentId}/¶

The only supported operation right now is segment restart, which removes existing child segment project and starts another child project instead for the given segment. Should be only used for child segments which are stuck during project startup or upload.

Code samples¶

# You can also use wget
curl -X PATCH https://app.datarobot.com/api/v2/projects/{projectId}/segments/{segmentId}/ \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{undefined}'

Body parameter¶

{
  "operation": "restart"
}

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID
segmentId	path	string	true	The name of the segment
body	body	ProjectSegmentUpdate	false	none

Example responses¶

{
  "projectId": "string",
  "segmentId": "string"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	The segment is updated.	ProjectSegmentUpdateResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/projects/{projectId}/status/¶

Check the status of a project

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/projects/{projectId}/status/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
projectId	path	string	true	The project ID.

Example responses¶

{
  "autopilotDone": true,
  "stage": "modeling",
  "stageDescription": "string"
}

Responses¶

Status	Meaning	Description	Schema
200	OK	The project status	ProjectStatusResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

Schemas¶

AccessControl

{
  "canShare": true,
  "role": "string",
  "userId": "string",
  "username": "string"
}

Properties¶

Name	Type	Required	Description
canShare	boolean	true	Whether the recipient can share the role further.
role	string	true	The role of the user on this entity.
userId	string	true	The identifier of the user that has access to this entity.
username	string	true	The username of the user that has access to the entity.

Aim

{
  "accuracyOptimizedMb": true,
  "aggregationType": "total",
  "allowPartialHistoryTimeSeriesPredictions": true,
  "allowedPairwiseInteractionGroups": [
    [
      "string",
      "string"
    ]
  ],
  "allowedPairwiseInteractionGroupsFilename": "string",
  "autopilotClusterList": [
    2
  ],
  "autopilotDataSamplingMethod": "random",
  "autopilotDataSelectionMethod": "duration",
  "autopilotWithFeatureDiscovery": true,
  "backtests": [
    {
      "gapDuration": "string",
      "index": 0,
      "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
      "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
      "validationDuration": "string",
      "validationEndDate": "2019-08-24T14:15:22Z",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "biasMitigationFeatureName": "string",
  "biasMitigationTechnique": "preprocessingReweighing",
  "blendBestModels": true,
  "blueprintThreshold": 1,
  "calendarId": "string",
  "chunkDefinitionId": "string",
  "classMappingAggregationSettings": {
    "aggregationClassName": "string",
    "excludedFromAggregation": [],
    "maxUnaggregatedClassValues": 1000,
    "minClassSupport": 1
  },
  "considerBlendersInRecommendation": true,
  "credentials": [
    {
      "catalogVersionId": "string",
      "password": "string",
      "url": "string",
      "user": "string"
    }
  ],
  "crossSeriesGroupByColumns": [
    "string"
  ],
  "cvHoldoutLevel": "string",
  "cvMethod": "random",
  "dateRemoval": true,
  "datetimePartitionColumn": "string",
  "datetimePartitioningId": "string",
  "defaultToAPriori": true,
  "defaultToDoNotDerive": true,
  "defaultToKnownInAdvance": true,
  "differencingMethod": "auto",
  "disableHoldout": false,
  "eventsCount": "string",
  "exponentiallyWeightedMovingAlpha": 1,
  "exposure": "string",
  "externalPredictions": [
    "string"
  ],
  "externalTimeSeriesBaselineDatasetId": "string",
  "externalTimeSeriesBaselineDatasetName": "string",
  "fairnessMetricsSet": "proportionalParity",
  "fairnessThreshold": 1,
  "featureDerivationWindowEnd": 0,
  "featureDerivationWindowStart": 0,
  "featureDiscoverySupervisedFeatureReduction": true,
  "featureEngineeringPredictionPoint": "string",
  "featureSettings": [
    {
      "aPriori": true,
      "doNotDerive": true,
      "featureName": "string",
      "knownInAdvance": true
    }
  ],
  "featurelistId": "string",
  "forecastDistance": "string",
  "forecastOffsets": [
    "string"
  ],
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "gapDuration": "string",
  "holdoutDuration": "string",
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutLevel": "string",
  "holdoutPct": 98,
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "includeBiasMitigationFeatureAsPredictorVariable": true,
  "incrementalLearningEarlyStoppingRounds": 0,
  "incrementalLearningOnBestModel": true,
  "incrementalLearningOnlyMode": true,
  "isHoldoutModified": true,
  "majorityDownsamplingRate": 0,
  "metric": "string",
  "minSecondaryValidationModelCount": 10,
  "mode": "0",
  "modelSplits": 5,
  "monotonicDecreasingFeaturelistId": "string",
  "monotonicIncreasingFeaturelistId": "string",
  "multiseriesIdColumns": [
    "string"
  ],
  "numberOfBacktests": 0,
  "numberOfIncrementalLearningIterationsBeforeBestModelSelection": 1,
  "offset": [
    "string"
  ],
  "onlyIncludeMonotonicBlueprints": false,
  "partitionKeyCols": [
    "string"
  ],
  "periodicities": [
    {
      "timeSteps": 0,
      "timeUnit": "MILLISECOND"
    }
  ],
  "positiveClass": "string",
  "preferableTargetValue": "string",
  "prepareModelForDeployment": true,
  "primaryLocationColumn": "string",
  "protectedFeatures": [
    "string"
  ],
  "quantileLevel": 0,
  "quickrun": true,
  "rateTopPctThreshold": 100,
  "relationshipsConfigurationId": "string",
  "reps": 2,
  "responseCap": 0.5,
  "runLeakageRemovedFeatureList": true,
  "sampleStepPct": 0,
  "scoringCodeOnly": true,
  "seed": 999999999,
  "segmentationTaskId": "string",
  "seriesId": "string",
  "shapOnlyMode": true,
  "smartDownsampled": true,
  "stopWords": [
    "string"
  ],
  "target": "string",
  "targetType": "Binary",
  "trainingLevel": "string",
  "treatAsExponential": "auto",
  "unsupervisedMode": false,
  "unsupervisedType": "anomaly",
  "useCrossSeriesFeatures": true,
  "useGpu": true,
  "useProjectSettings": true,
  "useSupervisedFeatureReduction": true,
  "useTimeSeries": false,
  "userPartitionCol": "string",
  "validationDuration": "string",
  "validationLevel": "string",
  "validationPct": 99,
  "validationType": "CV",
  "weights": "string",
  "windowsBasisUnit": "MILLISECOND"
}

Properties¶

Name	Type	Required	Restrictions	Description
accuracyOptimizedMb	boolean	false		Include additional, longer-running models that will be run by the autopilot and available to run manually.
aggregationType	string	false		For multiseries projects only. The aggregation type to apply when creating cross-series features.
allowPartialHistoryTimeSeriesPredictions	boolean	false		Specifies whether the time series predictions can use partial historical data.
allowedPairwiseInteractionGroups	[array]¦null	false	maxItems: 100	For GAM models - specify groups of columns for which pairwise interactions will be allowed. E.g. if set to [['A', 'B', 'C'], ['C', 'D']] then GAM models will allow interactions between columns AxB, BxC, AxC, CxD. All others (AxD, BxD) will not be considered. If not specified - all possible interactions will be considered by model.
allowedPairwiseInteractionGroupsFilename	string¦null	false		Filename that was used to upload allowed_pairwise_interaction_groups. Necessary for persistence of UI/UX when you specify that parameter via file.
autopilotClusterList	[integer]¦null	false	maxItems: 10	A list of integers where each value will be used as the number of clusters in Autopilot model(s) for unsupervised clustering projects. Cannot be specified unless `unsupervisedMode` is true and `unsupervisedType` is set to `clustering`.
autopilotDataSamplingMethod	string	false		Defines how autopilot will select subsample from training dataset in OTV/TS projects. Defaults to 'latest' for 'rowCount' dataSelectionMethod and to 'random' for 'duration'.
autopilotDataSelectionMethod	string	true		The Data Selection method to be used by autopilot when creating models for datetime-partitioned datasets.
autopilotWithFeatureDiscovery	boolean	false		If true, autopilot will run on a feature list that includes features found via search for interactions.
backtests	[Backtest]	false	maxItems: 50 minItems: 1	An array specifying the format of the backtests.
biasMitigationFeatureName	string	false	minLength: 1 minLength: 1	The name of the protected feature used to mitigate bias on models.
biasMitigationTechnique	string	false		Method applied to perform bias mitigation.
blendBestModels	boolean	false		Blend best models during Autopilot run. This option is not supported in SHAP-only mode or for multilabel projects.
blueprintThreshold	integer¦null	false	maximum: 1440 minimum: 1	The runtime (in hours) which if exceeded will exclude a model from autopilot runs.
calendarId	string	false		The ID of the calendar to be used in this project.
chunkDefinitionId	string	false		Chunk definition id for incremental learning using chunking service
classMappingAggregationSettings	ClassMappingAggregationSettings	false		Class mapping aggregation settings.
considerBlendersInRecommendation	boolean	false		Include blenders when selecting a model to prepare for deployment in an Autopilot Run. This option is not supported in SHAP-only mode or for multilabel projects.
credentials	[oneOf]	false	maxItems: 30	List of credentials for the secondary datasets used in feature discovery project.

oneOf

Name	Type	Required	Restrictions	Description
» anonymous	PasswordCredentials	false		none

xor

Name	Type	Required	Restrictions	Description
» anonymous	CredentialId	false		none

continued

Name	Type	Required	Restrictions	Description
crossSeriesGroupByColumns	[string]	false	maxItems: 1	For multiseries projects with cross-series features enabled only. List of columns (currently of length 1). Setting that indicates how to further split series into related groups. For example, if every series is sales of an individual product, the series group-by could be the product category with values like "men's clothing", "sports equipment", etc.
cvHoldoutLevel	any	false		The value of the partition column indicating a row is part of the holdout set. This level is optional - if not specified or if provided as `null`, then no holdout will be used in the project. The rest of the levels indicate which cross validation fold each row should fall into.

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	integer	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	number	false		none

continued

Name	Type	Required	Restrictions	Description
cvMethod	string	false		The partitioning method to be applied to the training data.
dateRemoval	boolean	false		If true, enable creating additional feature lists without dates (does not apply to time-aware projects).
datetimePartitionColumn	string	false		The date column that will be used as a datetime partition column.
datetimePartitioningId	string	false		The ID of a datetime partitioning to use for the project.When datetime_partitioning_id is specified, no other datetime partitioning related field is allowed to be specified, as these fields get loaded from the already created partitioning.
defaultToAPriori	boolean	false		Renamed to `defaultToKnownInAdvance`.
defaultToDoNotDerive	boolean	false		For time series projects only. Sets whether all features default to being treated as do-not-derive features, excluding them from feature derivation. Individual features can be set to a value different than the default by using the `featureSettings` parameter.
defaultToKnownInAdvance	boolean	false		For time series projects only. Sets whether all features default to being treated as known in advance features, which are features that are known into the future. Features marked as known in advance must be specified into the future when making predictions. The default is false, all features are not known in advance. Individual features can be set to a value different than the default using the `featureSettings` parameter. See the :ref:`Time Series Overview <time_series_overview>` for more context.
differencingMethod	string	false		For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems `simple` and `seasonal` are not allowed. Parameter `periodicities` must be specified if `seasonal` is chosen. Defaults to `auto`.
disableHoldout	boolean	false		Whether to suppress allocating a holdout fold. If `disableHoldout` is set to true, `holdoutStartDate` and `holdoutDuration` must not be set.
eventsCount	string	false		The name of a column specifying events count. The data in this column must be pure numeric and non negative without missing values
exponentiallyWeightedMovingAlpha	number	false	maximum: 1 minimum: 0	Discount factor (alpha) used for exponentially weighted moving features
exposure	string	false		The name of a column specifying row exposure.The data in this column must be pure numeric (e.g. not currency, date, length, etc.) and without missing values
externalPredictions	[string]	false	maxItems: 100 minItems: 1	List of external prediction columns from the dataset.
externalTimeSeriesBaselineDatasetId	string	false		Catalog version id for external prediction data that can be used as a baseline to calculate new metrics.
externalTimeSeriesBaselineDatasetName	string¦null	false		The name of the time series baseline dataset for the project.
fairnessMetricsSet	string	false		Metric to use for calculating fairness. Can be one of `proportionalParity`, `equalParity`, `predictionBalance`, `trueFavorableAndUnfavorableRateParity` or `FavorableAndUnfavorablePredictiveValueParity`. Used and required only if Bias & Fairness in AutoML feature is enabled.
fairnessThreshold	number	false	maximum: 1 minimum: 0	The threshold value of the fairness metric. The valid range is [0:1]; the default fairness metric value is 0.8. This metric is only applicable if the Bias & Fairness in AutoML feature is enabled.
featureDerivationWindowEnd	integer	false	maximum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the past relative to the forecast point the feature derivation window should end.
featureDerivationWindowStart	integer	false	maximum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the past relative to the forecast point the feature derivation window should begin.
featureDiscoverySupervisedFeatureReduction	boolean	false		Run supervised feature reduction for feature discovery projects.
featureEngineeringPredictionPoint	string¦null	false		The date column to be used as the prediction point for time-based feature engineering.
featureSettings	[FeatureSetting]	false		An array specifying per feature settings. Features can be left unspecified.
featurelistId	string	false		The ID of a featurelist to use for autopilot.
forecastDistance	string	false		The name of a column specifying the forecast distance to which each row of the dataset belongs. Column unique values are used to subset the modeling data and build a separate model for each unique column value. Similar to time series this column is well suited to be used as forecast distance.
forecastOffsets	[string]	false	maxItems: 100 minItems: 1	An array of strings with names of a columns specifying row offsets. Columns values are used as offset or predictions to boost for models. The data in this column must be pure numeric (e.g. not currency, date, length, etc.).
forecastWindowEnd	integer	false	minimum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the future relative to the forecast point the forecast window should end.
forecastWindowStart	integer	false	minimum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the future relative to the forecast point the forecast window should start.
gapDuration	string(duration)	false		The duration of the gap between holdout training and holdout scoring data. For time series projects, defaults to the duration of the gap between the end of the feature derivation window and the beginning of the forecast window. For OTV projects, defaults to a zero duration (P0Y0M0D).
holdoutDuration	string(duration)	false		The duration of holdout scoring data. When specifying `holdoutDuration`, `holdoutStartDate` must also be specified. This attribute cannot be specified when `disableHoldout` is true.
holdoutEndDate	string(date-time)	false		The end date of holdout scoring data. When specifying `holdoutEndDate`, `holdoutStartDate` must also be specified. This attribute cannot be specified when `disableHoldout` is true.
holdoutLevel	any	false		The value of the partition column indicating a row is part of the holdout set. This level is optional - if not specified or if provided as `null`, then no holdout will be used in the project. However, the column must have exactly 2 values in order for this option to be valid

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	integer	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	number	false		none

continued

Name	Type	Required	Restrictions	Description
holdoutPct	number	false	maximum: 98 minimum: 0	The percentage of the dataset to assign to the holdout set
holdoutStartDate	string(date-time)	false		The start date of holdout scoring data. When specifying `holdoutStartDate`, one of `holdoutEndDate` or `holdoutDuration` must also be specified. This attribute cannot be specified when `disableHoldout` is true.
includeBiasMitigationFeatureAsPredictorVariable	boolean	false		Specifies whether the mitigation feature will be used as a predictor variable (i.e., treated like other categorical features in the input to train the modeler), in addition to being used for bias mitigation. If false, the mitigation feature will be used only for bias mitigation, and not for training the modeler task.
incrementalLearningEarlyStoppingRounds	integer	false	minimum: 0	Early stopping rounds for the auto incremental learning service
incrementalLearningOnBestModel	boolean	false		Automatically run incremental learning on the best model during Autopilot run.
incrementalLearningOnlyMode	boolean	false		Keep only models that support incremental learning during Autopilot run.
isHoldoutModified	boolean	false		A boolean value indicating whether holdout settings (start/end dates) have been modified by user.
majorityDownsamplingRate	number	false		The percentage between 0 and 100 of the majority rows that should be kept. Must be specified only if using smart downsampling. If not specified, a default will be selected based on the dataset distribution. The chosen rate may not cause the majority class to become smaller than the minority class.
metric	string	false		The metric to use to select the best models. See `/api/v2/projects/(projectId)/features/metrics/` for the metrics that may be valid for a potential target. Note that weighted metrics must be used with a weights column.
minSecondaryValidationModelCount	integer	false	maximum: 10 minimum: 0	Compute 'All backtest' scores (datetime models) or cross validation scores for the specified number of highest ranking models on the Leaderboard, if over the Autopilot default.
mode	string	false		The autopilot mode to use. Either 'quick', 'auto', 'manual' or 'comprehensive'
modelSplits	integer	false	maximum: 10 minimum: 1	Sets the cap on the number of jobs per model used when building models to control number of jobs in the queue. Higher number of modelSplits will allow for less downsampling leading to the use of more post-processed data.
monotonicDecreasingFeaturelistId	string¦null	false		The ID of the featurelist that defines the set of features with a monotonically decreasing relationship to the target. If null, no such constraints are enforced. When specified, this will set a default for the project that can be overriden at model submission time if desired.
monotonicIncreasingFeaturelistId	string¦null	false		The ID of the featurelist that defines the set of features with a monotonically increasing relationship to the target. If null, no such constraints are enforced. When specified, this will set a default for the project that can be overriden at model submission time if desired.
multiseriesIdColumns	[string]	false	minItems: 1	May be used only with time series projects. An array of the column names identifying the series to which each row of the dataset belongs. Currently only one multiseries ID column is supported. See the :ref:`multiseries <multiseries>` section of the time series documentation for more context.
numberOfBacktests	integer	false		The number of backtests to use. If omitted, defaults to a positive value selected by the server based on the validation and gap durations.
numberOfIncrementalLearningIterationsBeforeBestModelSelection	integer	false	maximum: 10 minimum: 1	Number of incremental_learning iterations before best model selection.
offset	[string]	false		An array of strings with names of a columns specifying row offsets.The data in this column must be pure numeric (e.g. not currency, date, length, etc.) and without missing values
onlyIncludeMonotonicBlueprints	boolean	true		When true, only blueprints that support enforcing montonic constraints will be available in the project or selected for autopilot.
partitionKeyCols	[string]	false		An array containing a single string - the name of the group partition column
periodicities	[Periodicity]	false		A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing_method' will default to 'seasonal' if not provided or 'auto'.
positiveClass	any	false		A value from the target column to use for the positive class. May only be specified for projects doing binary classification.If not specified, a positive class is selected automatically.

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	integer	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	number	false		none

continued

Name	Type	Required	Restrictions	Description
preferableTargetValue	any	false		A target value that should be treated as a positive outcome for the prediction. For example if we want to check gender discrimination for giving a loan and our target named `is_bad`, then the positive outcome for the prediction would be `No`, which means that the loan is good and that's what we treat as a preferable result for the loaner. Used and required only if Bias & Fairness in AutoML feature is enabled.

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	integer	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	number	false		none

continued

Name	Type	Required	Restrictions	Description
prepareModelForDeployment	boolean	false		Prepare model for deployment during Autopilot run. The preparation includes creating reduced feature list models, retraining best model on higher sample size, computing insights and assigning 'RECOMMENDED FOR DEPLOYMENT' label.
primaryLocationColumn	string¦null	false		Primary geospatial location column.
protectedFeatures	[string]	false	maxItems: 10 minItems: 1	A list of project feature to mark as protected for Bias metric calculation and Fairness correction. Used and required only if Bias & Fairness in AutoML feature is enabled.
quantileLevel	number	false	maximum: 1 (exclusive) minimum: 0 (exclusive)	The quantile level between 0.01 and 0.99 for specifying the Quantile metric.
quickrun	boolean	false		(Deprecated): 'quick' should be used in the `mode` parameter instead of using this parameter. If set to `true`, autopilot mode will be set to 'quick'.Cannot be set to `true` when `mode` is set to 'comprehensive' or 'manual'.
rateTopPctThreshold	number	false	maximum: 100 minimum: 0	The percentage threshold between 0.1 and 50 for specifying the Rate@Top% metric.
relationshipsConfigurationId	string¦null	false		Relationships configuration id to be used for Feature Discovery projects.
reps	integer	false	maximum: 999999 minimum: 2	The number of cross validation folds to use.
responseCap	number	false	maximum: 1 minimum: 0.5	Used to cap the maximum response of a model
runLeakageRemovedFeatureList	boolean	false		Run Autopilot on Leakage Removed feature list (if exists).
sampleStepPct	number	false	maximum: 100 minimum: 0 (exclusive)	A float between 0 and 100 indicating the desired percentage of data to sample when training models in comprehensive Autopilot. Note: this only supported for comprehensive Autopilot and the specified value may be lowered in order to be compatible with the project's dataset and partition settings.
scoringCodeOnly	boolean	false		Keep only models that can be converted to scorable java code during Autopilot run.
seed	integer	false	maximum: 999999999 minimum: 0	A seed to use for randomization.
segmentationTaskId	string¦null	false		Specifies the SegmentationTask that will be used for dividing the project up into multiple segmented projects.
seriesId	string	false		The name of a column specifying the series ID to which each row of the dataset belongs. Typically the series was used to derive the additional features, that are independent from each other. Column unique values are used to subset the modeling data and build a separate model for each unique column value. Similar to time series this column is well suited to be used as multi-series ID column.
shapOnlyMode	boolean	false		Keep only models that support SHAP values during Autopilot run. Use SHAP-based insights wherever possible.
smartDownsampled	boolean	false		Whether to use smart downsampling to throw away excess rows of the majority class. Only applicable to classification and zero-boosted regression projects.
stopWords	[string]	false	maxItems: 1000	A list of stop words to be used for text blueprints. Note: `stop_words=True` must be set in the blueprint preprocessing parameters for this list of stop words to actually be used during preprocessing.
target	string	false		The name of the target feature.
targetType	string	false		Used to specify the targetType to use for a project when it is ambiguous, i.e. a numeric target with a few unique values that could be used for either regression or multiclass.
trainingLevel	any	false		The value of the partition column indicating a row is part of the training set.

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	integer	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	number	false		none

continued

Name	Type	Required	Description
treatAsExponential	string	false	For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems `always` is not allowed.
unsupervisedMode	boolean	false	If True, unsupervised project (without target) will be created. `target` cannot be specified if `unsupervisedMode` is True.
unsupervisedType	string¦null	false	The type of unsupervised project. Only valid when `unsupervisedMode` is true. If `unsupervisedMode`, defaults to `anomaly`.
useCrossSeriesFeatures	boolean	false	Indicating if user wants to use cross-series features.
useGpu	boolean	false	Indicates whether project should use GPU workers
useProjectSettings	boolean	false	Specifies whether datetime-partitioned project should use project settings (i.e. backtests configuration has been modified by the user).
useSupervisedFeatureReduction	boolean	false	When true, during feature generation DataRobot runs a supervised algorithm that identifies those features with predictive impact on the target and builds feature lists using only qualifying features. Setting false can severely impact autopilot duration, especially for datasets with many features.
useTimeSeries	boolean	false	A boolean value indicating whether a time series project should be created instead of a regular project which uses datetime partitioning.
userPartitionCol	string	false	The name of the column containing the partition assignments.
validationDuration	string(duration)	false	The default validation duration for all backtests. If the primary date/time feature in a time series project is irregular, you cannot set a default validation length. Instead, set each duration individually. For an OTV project setting the validation duration will always use regular partitioning. Omitting it will use irregular partitioning if the date/time feature is irregular.
validationLevel	any	false	The value of the partition column indicating a row is part of the validation set.

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	integer	false		none

or

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» anonymous	number	false		none

continued

Name	Type	Required	Restrictions	Description
validationPct	number	false	maximum: 99 minimum: 0	The percentage of the dataset to assign to the validation set
validationType	string	false		The validation method to be used. CV for cross validation or TVH for train-validation-holdout split.
weights	string	false		The name of a column specifying row weights. The data in this column must be pure numeric (e.g. not currency, date, length, etc.) and without missing values
windowsBasisUnit	string	false		For time series projects only. Indicates which unit is basis for feature derivation window and forecast window. Valid options are detected time unit or `ROW`. If omitted, the default value is detected time unit.

Enumerated Values¶

Property	Value
aggregationType	[`total`, `average`]
autopilotDataSamplingMethod	[`random`, `latest`]
autopilotDataSelectionMethod	[`duration`, `rowCount`]
biasMitigationTechnique	[`preprocessingReweighing`, `postProcessingRejectionOptionBasedClassification`]
cvMethod	[`random`, `user`, `stratified`, `group`, `datetime`]
differencingMethod	[`auto`, `none`, `simple`, `seasonal`]
fairnessMetricsSet	[`proportionalParity`, `equalParity`, `predictionBalance`, `trueFavorableAndUnfavorableRateParity`, `favorableAndUnfavorablePredictiveValueParity`]
mode	[`0`, `2`, `4`, `3`, `auto`, `manual`, `comprehensive`, `quick`]
targetType	[`Binary`, `Regression`, `Multiclass`, `Multilabel`]
treatAsExponential	[`auto`, `never`, `always`]
unsupervisedType	[`anomaly`, `clustering`]
validationType	[`CV`, `TVH`]
windowsBasisUnit	[`MILLISECOND`, `SECOND`, `MINUTE`, `HOUR`, `DAY`, `WEEK`, `MONTH`, `QUARTER`, `YEAR`, `ROW`]

AllowExtra

{}

Parameters submitted by the user to the failed job

Properties¶

None

Autopilot

{
  "command": "start"
}

Properties¶

Name	Type	Required	Restrictions	Description
command	string	true		If `start`, will unpause the autopilot and run queued jobs if workers are available. If `stop`, will pause the autopilot so no new jobs will be started.

Enumerated Values¶

Property	Value
command	[`start`, `stop`]

AutopilotStart

{
  "autopilotClusterList": [
    2
  ],
  "blendBestModels": true,
  "considerBlendersInRecommendation": true,
  "featurelistId": "string",
  "mode": "auto",
  "prepareModelForDeployment": true,
  "runLeakageRemovedFeatureList": true,
  "scoringCodeOnly": true,
  "useGpu": true
}

Properties¶

Name	Type	Required	Restrictions	Description
autopilotClusterList	[integer]¦null	false	maxItems: 10	Optional. A list of integers where each value will be used as the number of clusters in Autopilot model(s) for unsupervised clustering projects. Cannot be specified unless unsupervisedMode is true and unsupervisedType is set to 'clustering'.
blendBestModels	boolean	false		Blend best models during Autopilot run. This option is not supported in SHAP-only mode or for multilabel projects.
considerBlendersInRecommendation	boolean	false		Include blenders when selecting a model to prepare for deployment in an Autopilot Run. This option is not supported in SHAP-only mode or for multilabel projects.
featurelistId	string	true		The ID of a featurelist that should be used for autopilot.
mode	string	false		The autopilot mode.
prepareModelForDeployment	boolean	false		Prepare model for deployment during Autopilot run. The preparation includes creating reduced feature list models, retraining best model on higher sample size, computing insights and assigning "RECOMMENDED FOR DEPLOYMENT" label.
runLeakageRemovedFeatureList	boolean	false		Run Autopilot on Leakage Removed feature list (if exists).
scoringCodeOnly	boolean	false		Keep only models that can be converted to scorable java code during Autopilot run.
useGpu	boolean	false		Use GPU workers for Autopilot run.

Enumerated Values¶

Property	Value
mode	[`auto`, `comprehensive`, `quick`]

AzureServicePrincipalCredentials

{
  "azureTenantId": "string",
  "clientId": "string",
  "clientSecret": "string",
  "configId": "string",
  "credentialType": "azure_service_principal"
}

Properties¶

Name	Type	Required	Description
azureTenantId	string	false	Tenant ID of the Azure AD service principal.
clientId	string	false	Client ID of the Azure AD service principal.
clientSecret	string	false	Client Secret of the Azure AD service principal.
configId	string	false	ID of secure configurations of credentials shared by admin.
credentialType	string	true	The type of these credentials, 'azure_service_principal' here.

Enumerated Values¶

Property	Value
credentialType	`azure_service_principal`

Backtest

{
  "gapDuration": "string",
  "index": 0,
  "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
  "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
  "validationDuration": "string",
  "validationEndDate": "2019-08-24T14:15:22Z",
  "validationStartDate": "2019-08-24T14:15:22Z"
}

Properties¶

Name	Type	Required	Description
gapDuration	string(duration)	false	A duration string representing the duration of the gap between the training and the validation data for this backtest.
index	integer	true	The index from zero of the backtest specified by this object.
primaryTrainingEndDate	string(date-time)	false	A datetime string representing the end date of the primary training data for this backtest.
primaryTrainingStartDate	string(date-time)	false	A datetime string representing the start date of the primary training data for this backtest.
validationDuration	string(duration)	false	A duration string representing the duration of the validation data for this backtest.
validationEndDate	string(date-time)	false	A datetime string representing the end date of the validation data for this backtest.
validationStartDate	string(date-time)	true	A datetime string representing the start date of the validation data for this backtest.

BacktestNewMethodForOpenApi

{
  "index": 0,
  "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
  "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
  "validationEndDate": "2019-08-24T14:15:22Z",
  "validationStartDate": "2019-08-24T14:15:22Z"
}

Method 2 - directly configure the start and end dates of each partition, including the training partition.

Properties¶

Name	Type	Required	Description
index	integer	true	The index from zero of the backtest.
primaryTrainingEndDate	string(date-time)	true	A datetime string representing the end date of the primary training data for this backtest.
primaryTrainingStartDate	string(date-time)	true	A datetime string representing the start date of the primary training data for this backtest.
validationEndDate	string(date-time)	true	A datetime string representing the end date of the validation data for this backtest.
validationStartDate	string(date-time)	true	A datetime string representing the start date of the validation data for this backtest.

BacktestOldMethodForOpenApi

{
  "gapDuration": "string",
  "index": 0,
  "validationDuration": "string",
  "validationStartDate": "2019-08-24T14:15:22Z"
}

Method 1 - pass validation and gap durations

Properties¶

Name	Type	Required	Description
gapDuration	string(duration)	true	A duration string representing the duration of the gap between the training and the validation data for this backtest.
index	integer	true	The index from zero of the backtest.
validationDuration	string(duration)	true	A duration string representing the duration of the validation data for this backtest.
validationStartDate	string(date-time)	true	A datetime string representing the start date of the validation data for this backtest.

BacktestResponse

{
  "availableTrainingDuration": "string",
  "availableTrainingEndDate": "2019-08-24T14:15:22Z",
  "availableTrainingStartDate": "2019-08-24T14:15:22Z",
  "gapDuration": "string",
  "gapEndDate": "2019-08-24T14:15:22Z",
  "gapStartDate": "2019-08-24T14:15:22Z",
  "index": 0,
  "primaryTrainingDuration": "string",
  "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
  "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
  "validationDuration": "string",
  "validationEndDate": "2019-08-24T14:15:22Z",
  "validationStartDate": "2019-08-24T14:15:22Z"
}

Properties¶

Name	Type	Required	Description
availableTrainingDuration	string(duration)	true	The duration of the available training data for this backtest.
availableTrainingEndDate	string(date-time)	true	The end date of the available training data for this backtest.
availableTrainingStartDate	string(date-time)	true	The start date of the available training data for this backtest.
gapDuration	string(duration)	true	The duration of the gap between the training and the validation scoring data for this backtest.
gapEndDate	string(date-time)	true	The end date of the gap between the training and validation scoring data for this backtest.
gapStartDate	string(date-time)	true	The start date of the gap between the training and validation scoring data for this backtest.
index	integer	true	The index from zero of this backtest.
primaryTrainingDuration	string(duration)	true	The duration of the primary training data for this backtest.
primaryTrainingEndDate	string(date-time)	true	The end date of the primary training data for this backtest.
primaryTrainingStartDate	string(date-time)	true	The start date of the primary training data for this backtest.
validationDuration	string	true	The duration of the validation scoring data for this backtest.
validationEndDate	string(date-time)	true	The end date of the validation scoring data for this backtest.
validationStartDate	string(date-time)	true	The start date of the validation scoring data for this backtest.

Backtests

{
  "validationEndDate": "2019-08-24T14:15:22Z",
  "validationStartDate": "2019-08-24T14:15:22Z"
}

Properties¶

Name	Type	Required	Restrictions	Description
validationEndDate	string(date-time)	true		The end date of the validation scoring data for this backtest.
validationStartDate	string(date-time)	true		The start date of the validation scoring data for this backtest.

BasicCredentials

{
  "credentialType": "basic",
  "password": "string",
  "user": "string"
}

Properties¶

Name	Type	Required	Description
credentialType	string	true	The type of these credentials, 'basic' here.
password	string	true	The password for database authentication. The password is encrypted at rest and never saved / stored.
user	string	true	The username for database authentication.

Enumerated Values¶

Property	Value
credentialType	`basic`

ClassMappingAggregationSettings

{
  "aggregationClassName": "string",
  "excludedFromAggregation": [],
  "maxUnaggregatedClassValues": 1000,
  "minClassSupport": 1
}

Class mapping aggregation settings.

Properties¶

Name	Type	Required	Restrictions	Description
aggregationClassName	string	false		The name of the class that will be assigned to all rows with aggregated classes. Should not match any excluded_from_aggregation or we will have 2 classes with the same name and no way to distinguish between them. This option is only available formulticlass projects. By default 'DR_RARE_TARGET_VALUES' is used.
excludedFromAggregation	[string]	false		List of target values that should be guaranteed to kept as is, regardless of other settings.
maxUnaggregatedClassValues	integer	false	maximum: 1000 minimum: 3	The maximum number of unique labels before aggregation kicks in. Should be at least len(excludedFromAggregation) + 1 for multiclass and at least len(excludedFromAggregation) for multilabel.
minClassSupport	integer	false		Minimum number of instances necessary for each target value in the dataset. All values with fewer instances than this value will be aggregated

CredentialId

{
  "catalogVersionId": "string",
  "credentialId": "string",
  "url": "string"
}

Properties¶

Name	Type	Required	Description
catalogVersionId	string	false	The ID of the latest version of the catalog entry.
credentialId	string	true	The ID of the set of credentials to use instead of user and password. Note that with this change, username and password will become optional.
url	string	false	The link to retrieve more detailed information about the entity that uses this catalog dataset.

CrossSeriesGroupByColumnRetrieveResponse

{
  "crossSeriesGroupByColumns": [
    {
      "eligibility": "string",
      "isEligible": true,
      "name": "string"
    }
  ],
  "multiseriesId": "string"
}

Properties¶

Name	Type	Required	Restrictions	Description
crossSeriesGroupByColumns	[CrossSeriesGroupByColumnsListItem]	true		A list of columns with information about each column's eligibility as a cross-series group-by column.
multiseriesId	string	true		The name of the multiseries ID column.

CrossSeriesGroupByColumnsListItem

{
  "eligibility": "string",
  "isEligible": true,
  "name": "string"
}

Properties¶

Name	Type	Required	Description
eligibility	string	true	Information about the column's eligibility. If the column is not eligible, this will include the reason why.
isEligible	boolean	true	Indicates whether this column can be used as a group-by column.
name	string	true	The name of the column.

DatabricksAccessTokenCredentials

{
  "credentialType": "databricks_access_token_account",
  "databricksAccessToken": "string"
}

Properties¶

Name	Type	Required	Restrictions	Description
credentialType	string	true		The type of these credentials, 'databricks_access_token_account' here.
databricksAccessToken	string	true	minLength: 1 minLength: 1	Databricks personal access token.

Enumerated Values¶

Property	Value
credentialType	`databricks_access_token_account`

DatabricksServicePrincipalCredentials

{
  "clientId": "string",
  "clientSecret": "string",
  "configId": "string",
  "credentialType": "databricks_service_principal_account"
}

Properties¶

Name	Type	Required	Restrictions	Description
clientId	string	false	minLength: 1 minLength: 1	Client ID for Databricks service principal.
clientSecret	string	false	minLength: 1 minLength: 1	Client secret for Databricks service principal.
configId	string	false		The ID of the saved shared credentials. If specified, cannot include clientIdand clientSecret.
credentialType	string	true		The type of these credentials, 'databricks_service_principal_account' here.

Enumerated Values¶

Property	Value
credentialType	`databricks_service_principal_account`

DatetimePartitioningDataForOpenApi

{
  "aggregationType": "total",
  "allowPartialHistoryTimeSeriesPredictions": false,
  "autopilotClusterList": [
    2
  ],
  "autopilotDataSamplingMethod": "random",
  "autopilotDataSelectionMethod": "duration",
  "backtests": [
    {
      "gapDuration": "string",
      "index": 0,
      "validationDuration": "string",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "calendarId": "string",
  "clusteringBufferDisabled": false,
  "crossSeriesGroupByColumns": [
    "string"
  ],
  "datetimePartitionColumn": "string",
  "defaultToAPriori": true,
  "defaultToDoNotDerive": true,
  "defaultToKnownInAdvance": true,
  "differencingMethod": "auto",
  "disableHoldout": false,
  "featureDerivationWindowEnd": 0,
  "featureDerivationWindowStart": 0,
  "featureSettings": [
    {
      "aPriori": true,
      "doNotDerive": true,
      "featureName": "string",
      "knownInAdvance": true
    }
  ],
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "gapDuration": "string",
  "holdoutDuration": "string",
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "isHoldoutModified": true,
  "modelSplits": 5,
  "multiseriesIdColumns": [
    "string"
  ],
  "numberOfBacktests": 1,
  "periodicities": [
    {
      "timeSteps": 0,
      "timeUnit": "MILLISECOND"
    }
  ],
  "treatAsExponential": "auto",
  "unsupervisedMode": false,
  "unsupervisedType": "anomaly",
  "useCrossSeriesFeatures": false,
  "useSupervisedFeatureReduction": true,
  "useTimeSeries": false,
  "validationDuration": "string",
  "windowsBasisUnit": "MILLISECOND"
}

Properties¶

Name	Type	Required	Restrictions	Description
aggregationType	string	false		For multiseries projects only. The aggregation type to apply when creating cross-series features.
allowPartialHistoryTimeSeriesPredictions	boolean	false		Specifies whether the time series predictions can use partial historical data.
autopilotClusterList	[integer]¦null	false	maxItems: 10	A list of integers where each value will be used as the number of clusters in Autopilot model(s) for unsupervised clustering projects. Cannot be specified unless `unsupervisedMode` is true and `unsupervisedType` is set to `clustering`.
autopilotDataSamplingMethod	string	false		Defines how autopilot will select subsample from training dataset in OTV/TS projects. Defaults to 'latest' for 'rowCount' dataSelectionMethod and to 'random' for 'duration'.
autopilotDataSelectionMethod	string	false		The Data Selection method to be used by autopilot when creating models for datetime-partitioned datasets.
backtests	[oneOf]	false	maxItems: 20 minItems: 1	An array specifying individual backtests.

oneOf

Name	Type	Required	Restrictions	Description
» anonymous	BacktestOldMethodForOpenApi	false		Method 1 - pass validation and gap durations

xor

Name	Type	Required	Restrictions	Description
» anonymous	BacktestNewMethodForOpenApi	false		Method 2 - directly configure the start and end dates of each partition, including the training partition.

continued

Name	Type	Required	Restrictions	Description
calendarId	string	false		The ID of the calendar to be used in this project.
clusteringBufferDisabled	boolean	false		A boolean value indicating whether an clustering buffer creation should be disabled for unsupervised time series clustering project.
crossSeriesGroupByColumns	[string]	false	maxItems: 1	For multiseries projects with cross-series features enabled only. List of columns (currently of length 1). Setting that indicates how to further split series into related groups. For example, if every series is sales of an individual product, the series group-by could be the product category with values like "men's clothing", "sports equipment", etc.
datetimePartitionColumn	string	true		The date column that will be used as a datetime partition column.
defaultToAPriori	boolean	false		Renamed to `defaultToKnownInAdvance`.
defaultToDoNotDerive	boolean	false		For time series projects only. Sets whether all features default to being treated as do-not-derive features, excluding them from feature derivation. Individual features can be set to a value different than the default by using the `featureSettings` parameter.
defaultToKnownInAdvance	boolean	false		For time series projects only. Sets whether all features default to being treated as known in advance features, which are features that are known into the future. Features marked as known in advance must be specified into the future when making predictions. The default is false, all features are not known in advance. Individual features can be set to a value different than the default using the `featureSettings` parameter. See the :ref:`Time Series Overview <time_series_overview>` for more context.
differencingMethod	string	false		For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems `simple` and `seasonal` are not allowed. Parameter `periodicities` must be specified if `seasonal` is chosen. Defaults to `auto`.
disableHoldout	boolean	false		Whether to suppress allocating a holdout fold. If `disableHoldout` is set to true, `holdoutStartDate` and `holdoutDuration` must not be set.
featureDerivationWindowEnd	integer	false	maximum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the past relative to the forecast point the feature derivation window should end.
featureDerivationWindowStart	integer	false	maximum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the past relative to the forecast point the feature derivation window should begin.
featureSettings	[FeatureSetting]	false		An array specifying per feature settings. Features can be left unspecified.
forecastWindowEnd	integer	false	minimum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the future relative to the forecast point the forecast window should end.
forecastWindowStart	integer	false	minimum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the future relative to the forecast point the forecast window should start.
gapDuration	string(duration)	false		The duration of the gap between holdout training and holdout scoring data. For time series projects, defaults to the duration of the gap between the end of the feature derivation window and the beginning of the forecast window. For OTV projects, defaults to a zero duration (P0Y0M0D).
holdoutDuration	string(duration)	false		The duration of holdout scoring data. When specifying `holdoutDuration`, `holdoutStartDate` must also be specified. This attribute cannot be specified when `disableHoldout` is true.
holdoutEndDate	string(date-time)	false		The end date of holdout scoring data. When specifying `holdoutEndDate`, `holdoutStartDate` must also be specified. This attribute cannot be specified when `disableHoldout` is true.
holdoutStartDate	string(date-time)	false		The start date of holdout scoring data. When specifying `holdoutStartDate`, one of `holdoutEndDate` or `holdoutDuration` must also be specified. This attribute cannot be specified when `disableHoldout` is true.
isHoldoutModified	boolean	false		A boolean value indicating whether holdout settings (start/end dates) have been modified by user.
modelSplits	integer	false	maximum: 10 minimum: 1	Sets the cap on the number of jobs per model used when building models to control number of jobs in the queue. Higher number of modelSplits will allow for less downsampling leading to the use of more post-processed data.
multiseriesIdColumns	[string]	false	minItems: 1	May be used only with time series projects. An array of the column names identifying the series to which each row of the dataset belongs. Currently only one multiseries ID column is supported. See the :ref:`multiseries <multiseries>` section of the time series documentation for more context.
numberOfBacktests	integer	false	maximum: 20 minimum: 1	The number of backtests to use. If omitted, defaults to a positive value selected by the server based on the validation and gap durations.
periodicities	[Periodicity]	false		A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing_method' will default to 'seasonal' if not provided or 'auto'.
treatAsExponential	string	false		For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems `always` is not allowed. Defaults to `auto`.
unsupervisedMode	boolean	false		A boolean value indicating whether an unsupervised project should be created.
unsupervisedType	string¦null	false		The type of unsupervised project. Only valid when `unsupervisedMode` is true. If `unsupervisedMode`, defaults to `anomaly`.
useCrossSeriesFeatures	boolean	false		For multiseries projects only. Indicating whether to use cross-series features.
useSupervisedFeatureReduction	boolean	false		When true, during feature generation DataRobot runs a supervised algorithm that identifies those features with predictive impact on the target and builds feature lists using only qualifying features. Setting false can severely impact autopilot duration, especially for datasets with many features.
useTimeSeries	boolean	false		A boolean value indicating whether a time series project should be created instead of a regular project which uses datetime partitioning.
validationDuration	string(duration)	false		The default validation duration for all backtests. If the primary date/time feature in a time series project is irregular, you cannot set a default validation length. Instead, set each duration individually. For an OTV project setting the validation duration will always use regular partitioning. Omitting it will use irregular partitioning if the date/time feature is irregular.
windowsBasisUnit	string	false		For time series projects only. Indicates which unit is basis for feature derivation window and forecast window. Valid options are detected time unit or `ROW`. If omitted, the default value is detected time unit.

Enumerated Values¶

Property	Value
aggregationType	[`total`, `average`]
autopilotDataSamplingMethod	[`random`, `latest`]
autopilotDataSelectionMethod	[`duration`, `rowCount`]
differencingMethod	[`auto`, `none`, `simple`, `seasonal`]
treatAsExponential	[`auto`, `never`, `always`]
unsupervisedType	[`anomaly`, `clustering`]
windowsBasisUnit	[`MILLISECOND`, `SECOND`, `MINUTE`, `HOUR`, `DAY`, `WEEK`, `MONTH`, `QUARTER`, `YEAR`, `ROW`]

DatetimePartitioningLogListControllerResponse

{
  "count": 0,
  "datetimePartitioningLog": "string",
  "next": "http://example.com",
  "previous": "http://example.com",
  "totalLogLines": 0
}

Properties¶

Name	Type	Required	Description
count	integer	true	The number of items returned on this page.
datetimePartitioningLog	string	true	The content of the date/time partitioning log.
next	string(uri)¦null	true	URL pointing to the next page (if null, there is no next page).
previous	string(uri)¦null	true	URL pointing to the previous page (if null, there is no previous page).
totalLogLines	integer	true	The total number of lines in feature derivation log.

DatetimePartitioningResponse

{
  "aggregationType": "total",
  "allowPartialHistoryTimeSeriesPredictions": true,
  "autopilotDataSamplingMethod": "random",
  "autopilotDataSelectionMethod": "duration",
  "availableHoldoutEndDate": "2019-08-24T14:15:22Z",
  "availableTrainingDuration": "string",
  "availableTrainingEndDate": "2019-08-24T14:15:22Z",
  "availableTrainingStartDate": "2019-08-24T14:15:22Z",
  "backtests": [
    {
      "availableTrainingDuration": "string",
      "availableTrainingEndDate": "2019-08-24T14:15:22Z",
      "availableTrainingStartDate": "2019-08-24T14:15:22Z",
      "gapDuration": "string",
      "gapEndDate": "2019-08-24T14:15:22Z",
      "gapStartDate": "2019-08-24T14:15:22Z",
      "index": 0,
      "primaryTrainingDuration": "string",
      "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
      "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
      "validationDuration": "string",
      "validationEndDate": "2019-08-24T14:15:22Z",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "calendarId": "string",
  "calendarName": "string",
  "clusteringBufferDisabled": false,
  "crossSeriesGroupByColumns": [
    "string"
  ],
  "dateFormat": "string",
  "datetimePartitionColumn": "string",
  "datetimePartitioningId": "string",
  "defaultToAPriori": true,
  "defaultToDoNotDerive": true,
  "defaultToKnownInAdvance": true,
  "differencingMethod": "auto",
  "disableHoldout": true,
  "featureDerivationWindowEnd": 0,
  "featureDerivationWindowStart": 0,
  "featureSettings": [
    {
      "aPriori": true,
      "doNotDerive": true,
      "featureName": "string",
      "knownInAdvance": true
    }
  ],
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "gapDuration": "string",
  "gapEndDate": "2019-08-24T14:15:22Z",
  "gapStartDate": "2019-08-24T14:15:22Z",
  "holdoutDuration": "string",
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "isHoldoutModified": true,
  "modelSplits": 1,
  "multiseriesIdColumns": [
    "string"
  ],
  "numberOfBacktests": 1,
  "numberOfDoNotDeriveFeatures": 0,
  "numberOfKnownInAdvanceFeatures": 0,
  "partitioningExtendedWarnings": [
    {
      "backtestIndex": 0,
      "partition": "string",
      "warnings": [
        {
          "message": "string",
          "title": "string",
          "type": "string"
        }
      ]
    }
  ],
  "partitioningWarnings": [
    {
      "backtestIndex": 0,
      "partition": "string",
      "warnings": [
        "string"
      ]
    }
  ],
  "periodicities": [
    {
      "timeSteps": 0,
      "timeUnit": "MILLISECOND"
    }
  ],
  "primaryTrainingDuration": "string",
  "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
  "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
  "projectId": "string",
  "treatAsExponential": "auto",
  "unsupervisedMode": true,
  "unsupervisedType": "anomaly",
  "useCrossSeriesFeatures": true,
  "useTimeSeries": true,
  "validationDuration": "string",
  "windowsBasisUnit": "MILLISECOND"
}

Properties¶

Name	Type	Required	Restrictions	Description
aggregationType	string¦null	false		For multiseries projects only. The aggregation type to apply when creating cross-series features.
allowPartialHistoryTimeSeriesPredictions	boolean¦null	false		Specifies whether the time series predictions can use partial historical data.
autopilotDataSamplingMethod	string	true		The Data Sampling method to be used by autopilot when creating models for datetime-partitioned datasets.
autopilotDataSelectionMethod	string	true		The Data Selection method to be used by autopilot when creating models for datetime-partitioned datasets.
availableHoldoutEndDate	string(date-time)¦null	true		The maximum valid date of holdout scoring data.
availableTrainingDuration	string(duration)	true		The duration of available training duration for scoring the holdout.
availableTrainingEndDate	string(date-time)	true		The end date of available training data for scoring the holdout.
availableTrainingStartDate	string(date-time)	true		The start date of available training data for scoring the holdout.
backtests	[BacktestResponse]	true	maxItems: 20 minItems: 1	An array of the configured backtests.
calendarId	string¦null	false		The ID of the calendar to be used in this project.
calendarName	string¦null	false		The name of the calendar used in this project.
clusteringBufferDisabled	boolean	false		A boolean value indicating whether an clustering buffer creation should be disabled for unsupervised time series clustering project.
crossSeriesGroupByColumns	[string]¦null	false	maxItems: 1	For multiseries projects with cross-series features enabled only. List of columns (currently of length 1). Setting that indicates how to further split series into related groups. For example, if every series is sales of an individual product, the series group-by could be the product category with values like "men's clothing", "sports equipment", etc.
dateFormat	string	true		The date format of the partition column.
datetimePartitionColumn	string	true		The date column that will be used as a datetime partition column.
datetimePartitioningId	string	false		The ID of the current optimized datetime partitioning
defaultToAPriori	boolean	true		Renamed to `defaultToKnownInAdvance`.
defaultToDoNotDerive	boolean	true		For time series projects only. Sets whether all features default to being treated as do-not-derive features, excluding them from feature derivation. Individual features can be set to a value different than the default by using the `featureSettings` parameter.
defaultToKnownInAdvance	boolean	true		For time series projects only. Sets whether all features default to being treated as known in advance features, which are features that are known into the future. Features marked as known in advance must be specified into the future when making predictions. The default is false, all features are not known in advance. Individual features can be set to a value different than the default using the `featureSettings` parameter. See the :ref:`Time Series Overview <time_series_overview>` for more context.
differencingMethod	string¦null	true		For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems `simple` and `seasonal` are not allowed. Parameter `periodicities` must be specified if `seasonal` is chosen. Defaults to `auto`.
disableHoldout	boolean	true		A boolean value indicating whether date partitioning skipped allocating a holdout fold.
featureDerivationWindowEnd	integer¦null	true	maximum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the past relative to the forecast point the feature derivation window should end.
featureDerivationWindowStart	integer¦null	true	maximum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the past relative to the forecast point the feature derivation window should begin.
featureSettings	[FeatureSetting]	true		An array specifying per feature settings. Features can be left unspecified.
forecastWindowEnd	integer¦null	true	minimum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the future relative to the forecast point the forecast window should end.
forecastWindowStart	integer¦null	true	minimum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the future relative to the forecast point the forecast window should start.
gapDuration	string(duration)	true		The duration of the gap between the training and holdout scoring data.
gapEndDate	string(date-time)	true		The end date of the gap between the training and holdout scoring data.
gapStartDate	string(date-time)	true		The start date of the gap between the training and holdout scoring data.
holdoutDuration	string(duration)	true		The duration of the holdout scoring data.
holdoutEndDate	string(date-time)	true		The end date of holdout scoring data.
holdoutStartDate	string(date-time)	true		The start date of holdout scoring data.
isHoldoutModified	boolean	false		A boolean value indicating whether holdout settings (start/end dates) have been modified by user.
modelSplits	integer	false	maximum: 10 minimum: 1	Sets the cap on the number of jobs per model used when building models to control number of jobs in the queue. Higher number of modelSplits will allow for less downsampling leading to the use of more post-processed data.
multiseriesIdColumns	[string]¦null	true	minItems: 1	May be used only with time series projects. An array of the column names identifying the series to which each row of the dataset belongs. Currently only one multiseries ID column is supported. See the :ref:`multiseries <multiseries>` section of the time series documentation for more context.
numberOfBacktests	integer	true	maximum: 20 minimum: 1	The number of backtests to use. If omitted, defaults to a positive value selected by the server based on the validation and gap durations.
numberOfDoNotDeriveFeatures	integer	true		Number of features that are marked as "do not derive".
numberOfKnownInAdvanceFeatures	integer	true		Number of features that are marked as "known in advance".
partitioningExtendedWarnings	[PartitioningExtendedWarning]	false		An array of available warnings about potential problems with the chosen partitioning that could cause issues during modeling, although the partitioning may be successfully submitted.
partitioningWarnings	[PartitioningWarning]	true		An array of available warnings about potential problems with the chosen partitioning that could cause issues during modeling, although the partitioning may be successfully submitted.
periodicities	[Periodicity]¦null	true		A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing_method' will default to 'seasonal' if not provided or 'auto'.
primaryTrainingDuration	string(duration)	true		The duration of primary training duration for scoring the holdout.
primaryTrainingEndDate	string(date-time)	true		The end date of primary training data for scoring the holdout.
primaryTrainingStartDate	string(date-time)	true		The start date of primary training data for scoring the holdout.
projectId	string	true		The ID of the project.
treatAsExponential	string¦null	true		For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems `always` is not allowed. Defaults to `auto`.
unsupervisedMode	boolean¦null	false		A boolean value indicating whether an unsupervised project should be created.
unsupervisedType	string¦null	false		The type of unsupervised project.
useCrossSeriesFeatures	boolean¦null	false		For multiseries projects only. Indicating whether to use cross-series features.
useTimeSeries	boolean	true		A boolean value indicating whether a time series project should be created instead of a regular project which uses datetime partitioning.
validationDuration	string(duration)¦null	true		The default validation duration for all backtests. If the primary date/time feature in a time series project is irregular, you cannot set a default validation length. Instead, set each duration individually.
windowsBasisUnit	string¦null	true		For time series projects only. Indicates which unit is basis for feature derivation window and forecast window. Valid options are detected time unit or `ROW`. If omitted, the default value is detected time unit.

Enumerated Values¶

Property	Value
aggregationType	[`total`, `average`]
autopilotDataSamplingMethod	[`random`, `latest`]
autopilotDataSelectionMethod	[`duration`, `rowCount`]
differencingMethod	[`auto`, `none`, `simple`, `seasonal`]
treatAsExponential	[`auto`, `never`, `always`]
unsupervisedType	[`anomaly`, `clustering`]
windowsBasisUnit	[`MILLISECOND`, `SECOND`, `MINUTE`, `HOUR`, `DAY`, `WEEK`, `MONTH`, `QUARTER`, `YEAR`, `ROW`]

DeletedProjectCountResponse

{
  "deletedProjectsCount": 0,
  "projectCountLimit": 0,
  "valueExceedsLimit": true
}

Properties¶

Name	Type	Required	Restrictions	Description
deletedProjectsCount	integer	true	minimum: 0	Amount of soft-deleted projects. The value is limited by projectCountLimit
projectCountLimit	integer	true	minimum: 0	Deleted projects counting limit value. Stop counting above this limit
valueExceedsLimit	boolean	true		If an actual number of soft-deleted projects exceeds counting limit

DeletedProjectListResponse

{
  "count": 0,
  "data": [
    {
      "createdBy": {
        "email": "string",
        "id": "string"
      },
      "deletedBy": {
        "email": "string",
        "id": "string"
      },
      "deletionTime": "2019-08-24T14:15:22Z",
      "fileName": "string",
      "id": "string",
      "organization": {
        "id": "string",
        "name": "string"
      },
      "projectName": "Untitled Project",
      "scheduledForDeletion": true
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Properties¶

Name	Type	Required	Description
count	integer	false	Number of items returned on this page.
data	[DeletedProjectResponse]	true	List of deleted projects
next	string(uri)¦null	true	URL pointing to the next page (if null, there is no next page).
previous	string(uri)¦null	true	URL pointing to the previous page (if null, there is no previous page).

DeletedProjectOrganization

{
  "id": "string",
  "name": "string"
}

The organization the project belongs to

Properties¶

Name	Type	Required	Restrictions	Description
id	string	true		ID of the organization the project belongs to
name	string	true		Name of the organization the project belongs to

DeletedProjectResponse

{
  "createdBy": {
    "email": "string",
    "id": "string"
  },
  "deletedBy": {
    "email": "string",
    "id": "string"
  },
  "deletionTime": "2019-08-24T14:15:22Z",
  "fileName": "string",
  "id": "string",
  "organization": {
    "id": "string",
    "name": "string"
  },
  "projectName": "Untitled Project",
  "scheduledForDeletion": true
}

Properties¶

Name	Type	Required	Description
createdBy	DeletedProjectUser	true	The user who created the project
deletedBy	DeletedProjectUser	true	The user who created the project
deletionTime	string(date-time)¦null	true	ISO-8601 formatted date when project was deleted
fileName	string¦null	true	The name of the file uploaded for the project dataset
id	string	true	The ID of the project
organization	DeletedProjectOrganization	true	The organization the project belongs to
projectName	string	true	The name of the project
scheduledForDeletion	boolean	true	Whether project permanent deletion has already been scheduled

DeletedProjectUser

{
  "email": "string",
  "id": "string"
}

The user who created the project

Properties¶

Name	Type	Required	Restrictions	Description
email	string	true		Email of the user
id	string	true		ID of the user

ExternalTSBaselineMetadata

{
  "datasetId": "string",
  "datasetName": "string"
}

The id of the catalog item that is being used as the external baseline data

Properties¶

Name	Type	Required	Restrictions	Description
datasetId	string¦null	true		Catalog version id for external prediction data that can be used as a baseline to calculate new metrics.
datasetName	string¦null	true		The name of the timeseries baseline dataset for the project

ExternalTSBaselinePayload

{
  "backtests": [
    {
      "validationEndDate": "2019-08-24T14:15:22Z",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "catalogVersionId": "string",
  "datetimePartitionColumn": "string",
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "multiseriesIdColumns": [
    "string"
  ],
  "target": "string"
}

Properties¶

Name	Type	Required	Restrictions	Description
backtests	[Backtests]	false	maxItems: 20 minItems: 1	An array of the configured backtests.
catalogVersionId	string	true		The version id of the external baseline data item in the AI catalog.
datetimePartitionColumn	string	true		The date column that will be used as the datetime partition column for the specified project.
forecastWindowEnd	integer	true	minimum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the future relative to the forecast point the forecast window should end.
forecastWindowStart	integer	true	minimum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the future relative to the forecast point the forecast window should start.
holdoutEndDate	string(date-time)	false		The end date of holdout scoring data.
holdoutStartDate	string(date-time)	false		The start date of holdout scoring data.
multiseriesIdColumns	[string]	false	maxItems: 1 minItems: 1	An array of column names identifying the multiseries ID column(s)to use to identify series within the data. Must match the multiseries ID column(s) for the specified project. Currently, only one multiseries ID column may be specified.
target	string	true		The selected target of the specified project.

ExternalTSBaselineResponse

{
  "backtests": [
    {
      "validationEndDate": "2019-08-24T14:15:22Z",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "baselineValidationJobId": "string",
  "catalogVersionId": "string",
  "datetimePartitionColumn": "string",
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "isExternalBaselineDatasetValid": true,
  "message": "string",
  "multiseriesIdColumns": [
    "string"
  ],
  "projectId": "string",
  "target": "string"
}

Properties¶

Name	Type	Required	Restrictions	Description
backtests	[Backtests]	false	maxItems: 20 minItems: 1	An array of the configured backtests.
baselineValidationJobId	string	true		The id of the validation job.
catalogVersionId	string	true		The version id of the external baseline data item in the AI catalog.
datetimePartitionColumn	string	true		The date column that will be used as the datetime partition column for the specified project.
forecastWindowEnd	integer	false	minimum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the future relative to the forecast point the forecast window should end.
forecastWindowStart	integer	false	minimum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the future relative to the forecast point the forecast window should start.
holdoutEndDate	string(date-time)	false		The end date of holdout scoring data.
holdoutStartDate	string(date-time)	false		The start date of holdout scoring data.
isExternalBaselineDatasetValid	boolean	true		Indicates whether the external dataset has pass the validation check or not.
message	string¦null	true		A message providing mode detail on the validation result.
multiseriesIdColumns	[string]	false	maxItems: 1 minItems: 1	An array of column names identifying the multiseries ID column(s)to use to identify series within the data. Must match the multiseries ID column(s) for the specified project. Currently, only one multiseries ID column may be specified.
projectId	string	true		The project id of the external baseline data item.
target	string	true		The selected target of the specified project.

FeatureSetting

{
  "aPriori": true,
  "doNotDerive": true,
  "featureName": "string",
  "knownInAdvance": true
}

Properties¶

Name	Type	Required	Description
aPriori	boolean	false	Renamed to `knownInAdvance`.
doNotDerive	boolean	false	For time series projects only. Sets whether the feature is do-not-derive, i.e., is excluded from feature derivation. If not specified, the feature uses the value from the `defaultToDoNotDerive` flag.
featureName	string	true	The name of the feature being specified.
knownInAdvance	boolean	false	For time series projects only. Sets whether the feature is known in advance, i.e., values for future dates are known at prediction time. If not specified, the feature uses the value from the `defaultToKnownInAdvance` flag.

FinalBacktestResponse

{
  "availableTrainingDuration": "string",
  "availableTrainingEndDate": "2019-08-24T14:15:22Z",
  "availableTrainingRowCount": 0,
  "availableTrainingStartDate": "2019-08-24T14:15:22Z",
  "gapDuration": "string",
  "gapEndDate": "2019-08-24T14:15:22Z",
  "gapRowCount": 0,
  "gapStartDate": "2019-08-24T14:15:22Z",
  "index": 0,
  "primaryTrainingDuration": "string",
  "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
  "primaryTrainingRowCount": 0,
  "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
  "totalRowCount": 0,
  "validationDuration": "string",
  "validationEndDate": "2019-08-24T14:15:22Z",
  "validationRowCount": 0,
  "validationStartDate": "2019-08-24T14:15:22Z"
}

Properties¶

Name	Type	Required	Description
availableTrainingDuration	string(duration)	true	The duration of the available training data for this backtest.
availableTrainingEndDate	string(date-time)	true	The end date of the available training data for this backtest.
availableTrainingRowCount	integer	true	The number of rows in the available training data for this backtest.
availableTrainingStartDate	string(date-time)	true	The start date of the available training data for this backtest.
gapDuration	string(duration)	true	The duration of the gap between the training and the validation scoring data for this backtest.
gapEndDate	string(date-time)	true	The end date of the gap between the training and validation scoring data for this backtest.
gapRowCount	integer	true	The number of rows in the gap between the training and the validation scoring data for this backtest.
gapStartDate	string(date-time)	true	The start date of the gap between the training and validation scoring data for this backtest.
index	integer	true	The index from zero of this backtest.
primaryTrainingDuration	string(duration)	true	The duration of the primary training data for this backtest.
primaryTrainingEndDate	string(date-time)	true	The end date of the primary training data for this backtest.
primaryTrainingRowCount	integer	true	The number of rows in the primary training data for this backtest.
primaryTrainingStartDate	string(date-time)	true	The start date of the primary training data for this backtest.
totalRowCount	integer	true	The total number of rows in this backtest
validationDuration	string	true	The duration of the validation scoring data for this backtest.
validationEndDate	string(date-time)	true	The end date of the validation scoring data for this backtest.
validationRowCount	integer	true	The number of rows in the validation scoring data for this backtest.
validationStartDate	string(date-time)	true	The start date of the validation scoring data for this backtest.

FinalDatetimePartitioningResponse

{
  "aggregationType": "total",
  "allowPartialHistoryTimeSeriesPredictions": true,
  "autopilotDataSamplingMethod": "random",
  "autopilotDataSelectionMethod": "duration",
  "availableHoldoutEndDate": "2019-08-24T14:15:22Z",
  "availableTrainingDuration": "string",
  "availableTrainingEndDate": "2019-08-24T14:15:22Z",
  "availableTrainingRowCount": 0,
  "availableTrainingStartDate": "2019-08-24T14:15:22Z",
  "backtests": [
    {
      "availableTrainingDuration": "string",
      "availableTrainingEndDate": "2019-08-24T14:15:22Z",
      "availableTrainingRowCount": 0,
      "availableTrainingStartDate": "2019-08-24T14:15:22Z",
      "gapDuration": "string",
      "gapEndDate": "2019-08-24T14:15:22Z",
      "gapRowCount": 0,
      "gapStartDate": "2019-08-24T14:15:22Z",
      "index": 0,
      "primaryTrainingDuration": "string",
      "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
      "primaryTrainingRowCount": 0,
      "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
      "totalRowCount": 0,
      "validationDuration": "string",
      "validationEndDate": "2019-08-24T14:15:22Z",
      "validationRowCount": 0,
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "calendarId": "string",
  "calendarName": "string",
  "crossSeriesGroupByColumns": [
    "string"
  ],
  "dateFormat": "string",
  "datetimePartitionColumn": "string",
  "datetimePartitioningId": "string",
  "defaultToAPriori": true,
  "defaultToDoNotDerive": true,
  "defaultToKnownInAdvance": true,
  "differencingMethod": "auto",
  "disableHoldout": true,
  "featureDerivationWindowEnd": 0,
  "featureDerivationWindowStart": 0,
  "featureSettings": [
    {
      "aPriori": true,
      "doNotDerive": true,
      "featureName": "string",
      "knownInAdvance": true
    }
  ],
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "gapDuration": "string",
  "gapEndDate": "2019-08-24T14:15:22Z",
  "gapRowCount": 0,
  "gapStartDate": "2019-08-24T14:15:22Z",
  "holdoutDuration": "string",
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutRowCount": 0,
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "isHoldoutModified": true,
  "modelSplits": 1,
  "multiseriesIdColumns": [
    "string"
  ],
  "numberOfBacktests": 1,
  "numberOfDoNotDeriveFeatures": 0,
  "numberOfKnownInAdvanceFeatures": 0,
  "partitioningExtendedWarnings": [
    {
      "backtestIndex": 0,
      "partition": "string",
      "warnings": [
        {
          "message": "string",
          "title": "string",
          "type": "string"
        }
      ]
    }
  ],
  "partitioningWarnings": [
    {
      "backtestIndex": 0,
      "partition": "string",
      "warnings": [
        "string"
      ]
    }
  ],
  "periodicities": [
    {
      "timeSteps": 0,
      "timeUnit": "MILLISECOND"
    }
  ],
  "primaryTrainingDuration": "string",
  "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
  "primaryTrainingRowCount": 0,
  "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
  "projectId": "string",
  "totalRowCount": 0,
  "treatAsExponential": "auto",
  "unsupervisedMode": true,
  "unsupervisedType": "anomaly",
  "useCrossSeriesFeatures": true,
  "useTimeSeries": true,
  "validationDuration": "string",
  "windowsBasisUnit": "MILLISECOND"
}

Properties¶

Name	Type	Required	Restrictions	Description
aggregationType	string¦null	true		For multiseries projects only. The aggregation type to apply when creating cross-series features.
allowPartialHistoryTimeSeriesPredictions	boolean¦null	false		Specifies whether the time series predictions can use partial historical data.
autopilotDataSamplingMethod	string	true		The Data Sampling method to be used by autopilot when creating models for datetime-partitioned datasets.
autopilotDataSelectionMethod	string	true		The Data Selection method to be used by autopilot when creating models for datetime-partitioned datasets.
availableHoldoutEndDate	string(date-time)¦null	true		The maximum valid date of holdout scoring data.
availableTrainingDuration	string(duration)	true		The duration of available training duration for scoring the holdout.
availableTrainingEndDate	string(date-time)	true		The end date of available training data for scoring the holdout.
availableTrainingRowCount	integer	true		The number of rows in the available training data for scoring the holdout partition
availableTrainingStartDate	string(date-time)	true		The start date of available training data for scoring the holdout.
backtests	[FinalBacktestResponse]	true	maxItems: 20 minItems: 1	An array of the configured backtests.
calendarId	string¦null	true		The ID of the calendar to be used in this project.
calendarName	string¦null	true		The name of the calendar used in this project.
crossSeriesGroupByColumns	[string]¦null	true	maxItems: 1	For multiseries projects with cross-series features enabled only. List of columns (currently of length 1). Setting that indicates how to further split series into related groups. For example, if every series is sales of an individual product, the series group-by could be the product category with values like "men's clothing", "sports equipment", etc.
dateFormat	string	true		The date format of the partition column.
datetimePartitionColumn	string	true		The date column that will be used as a datetime partition column.
datetimePartitioningId	string	false		The ID of the current optimized datetime partitioning
defaultToAPriori	boolean	true		Renamed to `defaultToKnownInAdvance`.
defaultToDoNotDerive	boolean	true		For time series projects only. Sets whether all features default to being treated as do-not-derive features, excluding them from feature derivation. Individual features can be set to a value different than the default by using the `featureSettings` parameter.
defaultToKnownInAdvance	boolean	true		For time series projects only. Sets whether all features default to being treated as known in advance features, which are features that are known into the future. Features marked as known in advance must be specified into the future when making predictions. The default is false, all features are not known in advance. Individual features can be set to a value different than the default using the `featureSettings` parameter. See the :ref:`Time Series Overview <time_series_overview>` for more context.
differencingMethod	string¦null	true		For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems `simple` and `seasonal` are not allowed. Parameter `periodicities` must be specified if `seasonal` is chosen. Defaults to `auto`.
disableHoldout	boolean	true		A boolean value indicating whether date partitioning skipped allocating a holdout fold.
featureDerivationWindowEnd	integer¦null	true	maximum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the past relative to the forecast point the feature derivation window should end.
featureDerivationWindowStart	integer¦null	true	maximum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the past relative to the forecast point the feature derivation window should begin.
featureSettings	[FeatureSetting]	true		An array specifying per feature settings. Features can be left unspecified.
forecastWindowEnd	integer¦null	true	minimum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the future relative to the forecast point the forecast window should end.
forecastWindowStart	integer¦null	true	minimum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the future relative to the forecast point the forecast window should start.
gapDuration	string(duration)	true		The duration of the gap between the training and holdout scoring data.
gapEndDate	string(date-time)	true		The end date of the gap between the training and holdout scoring data.
gapRowCount	integer	true		The number of rows in the gap between the training and holdout scoring data
gapStartDate	string(date-time)	true		The start date of the gap between the training and holdout scoring data.
holdoutDuration	string(duration)	true		The duration of the holdout scoring data.
holdoutEndDate	string(date-time)	true		The end date of holdout scoring data.
holdoutRowCount	integer	true		The number of rows in the holdout scoring data
holdoutStartDate	string(date-time)	true		The start date of holdout scoring data.
isHoldoutModified	boolean	false		A boolean value indicating whether holdout settings (start/end dates) have been modified by user.
modelSplits	integer¦null	true	maximum: 10 minimum: 1	Sets the cap on the number of jobs per model used when building models to control number of jobs in the queue. Higher number of modelSplits will allow for less downsampling leading to the use of more post-processed data.
multiseriesIdColumns	[string]¦null	true	minItems: 1	May be used only with time series projects. An array of the column names identifying the series to which each row of the dataset belongs. Currently only one multiseries ID column is supported. See the :ref:`multiseries <multiseries>` section of the time series documentation for more context.
numberOfBacktests	integer	true	maximum: 20 minimum: 1	The number of backtests to use. If omitted, defaults to a positive value selected by the server based on the validation and gap durations.
numberOfDoNotDeriveFeatures	integer	true		Number of features that are marked as "do not derive".
numberOfKnownInAdvanceFeatures	integer	true		Number of features that are marked as "known in advance".
partitioningExtendedWarnings	[PartitioningExtendedWarning]	false		An array of available warnings about potential problems with the chosen partitioning that could cause issues during modeling, although the partitioning may be successfully submitted.
partitioningWarnings	[PartitioningWarning]	true		An array of available warnings about potential problems with the chosen partitioning that could cause issues during modeling, although the partitioning may be successfully submitted.
periodicities	[Periodicity]¦null	true		A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing_method' will default to 'seasonal' if not provided or 'auto'.
primaryTrainingDuration	string(duration)	true		The duration of primary training duration for scoring the holdout.
primaryTrainingEndDate	string(date-time)	true		The end date of primary training data for scoring the holdout.
primaryTrainingRowCount	integer	true		The number of rows in the primary training data for scoring the holdout
primaryTrainingStartDate	string(date-time)	true		The start date of primary training data for scoring the holdout.
projectId	string	true		The ID of the project.
totalRowCount	integer	true		The total number of rows in the project dataset
treatAsExponential	string¦null	true		For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems `always` is not allowed. Defaults to `auto`.
unsupervisedMode	boolean¦null	false		A boolean value indicating whether an unsupervised project should be created.
unsupervisedType	string¦null	false		The type of unsupervised project.
useCrossSeriesFeatures	boolean¦null	true		For multiseries projects only. Indicating whether to use cross-series features.
useTimeSeries	boolean	true		A boolean value indicating whether a time series project should be created instead of a regular project which uses datetime partitioning.
validationDuration	string(duration)¦null	true		The default validation duration for all backtests. If the primary date/time feature in a time series project is irregular, you cannot set a default validation length. Instead, set each duration individually.
windowsBasisUnit	string¦null	true		For time series projects only. Indicates which unit is basis for feature derivation window and forecast window. Valid options are detected time unit or `ROW`. If omitted, the default value is detected time unit.

Enumerated Values¶

Property	Value
aggregationType	[`total`, `average`]
autopilotDataSamplingMethod	[`random`, `latest`]
autopilotDataSelectionMethod	[`duration`, `rowCount`]
differencingMethod	[`auto`, `none`, `simple`, `seasonal`]
treatAsExponential	[`auto`, `never`, `always`]
unsupervisedType	[`anomaly`, `clustering`]
windowsBasisUnit	[`MILLISECOND`, `SECOND`, `MINUTE`, `HOUR`, `DAY`, `WEEK`, `MONTH`, `QUARTER`, `YEAR`, `ROW`]

GCPKey

{
  "authProviderX509CertUrl": "http://example.com",
  "authUri": "http://example.com",
  "clientEmail": "string",
  "clientId": "string",
  "clientX509CertUrl": "http://example.com",
  "privateKey": "string",
  "privateKeyId": "string",
  "projectId": "string",
  "tokenUri": "http://example.com",
  "type": "service_account"
}

The Google Cloud Platform (GCP) key. Output is the downloaded JSON resulting from creating a service account User Managed Key (in the IAM & admin > Service accounts section of GCP).Required if googleConfigId/configId is not specified.Cannot include this parameter if googleConfigId/configId is specified.

Properties¶

Name	Type	Required	Description
authProviderX509CertUrl	string(uri)	false	Auth provider X509 certificate URL.
authUri	string(uri)	false	Auth URI.
clientEmail	string	false	Client email address.
clientId	string	false	Client ID.
clientX509CertUrl	string(uri)	false	Client X509 certificate URL.
privateKey	string	false	Private key.
privateKeyId	string	false	Private key ID
projectId	string	false	Project ID.
tokenUri	string(uri)	false	Token URI.
type	string	true	GCP account type.

Enumerated Values¶

Property	Value
type	`service_account`

GoogleServiceAccountCredentials

{
  "configId": "string",
  "credentialType": "gcp",
  "gcpKey": {
    "authProviderX509CertUrl": "http://example.com",
    "authUri": "http://example.com",
    "clientEmail": "string",
    "clientId": "string",
    "clientX509CertUrl": "http://example.com",
    "privateKey": "string",
    "privateKeyId": "string",
    "projectId": "string",
    "tokenUri": "http://example.com",
    "type": "service_account"
  },
  "googleConfigId": "string"
}

Properties¶

Name	Type	Required	Description
configId	string	false	ID of Secure configurations shared by admin.Alternative to googleConfigId (deprecated). If specified, cannot include gcpKey.
credentialType	string	true	The type of these credentials, 'gcp' here.
gcpKey	GCPKey	false	The Google Cloud Platform (GCP) key. Output is the downloaded JSON resulting from creating a service account User Managed Key (in the IAM & admin > Service accounts section of GCP).Required if googleConfigId/configId is not specified.Cannot include this parameter if googleConfigId/configId is specified.
googleConfigId	string	false	ID of Secure configurations shared by admin. This is deprecated.Please use configId instead. If specified, cannot include gcpKey.

Enumerated Values¶

Property	Value
credentialType	`gcp`

HdfsProjectCreate

{
  "password": "string",
  "port": 0,
  "projectName": "string",
  "url": "http://example.com",
  "user": "string"
}

Properties¶

Name	Type	Required	Description
password	string	false	Password for authenticating to HDFS using Kerberos. The password will be encrypted on the server side in scope of HTTP request and never saved or stored.
port	integer	false	Port of the WebHDFS Namenode server. If not specified, defaults to HDFS default port 50070.
projectName	string	false	Name of the project to be created. If not specified, project name will be based on the file name.
url	string(uri)	true	URL of the WebHDFS resource. Represent the file using the `hdfs://` protocol marker (for example, `hdfs:///tmp/somedataset.csv`).
user	string	false	Username for authenticating to HDFS using Kerberos

JobDetailsResponse

{
  "id": "string",
  "isBlocked": true,
  "jobType": "model",
  "message": "string",
  "modelId": "string",
  "projectId": "string",
  "status": "queue",
  "url": "string"
}

Properties¶

Name	Type	Required	Description
id	string	true	The job ID.
isBlocked	boolean	true	True if the job is waiting for its dependencies to be resolved first.
jobType	string	true	The job type.
message	string	true	Error message in case of failure.
modelId	string	true	The model this job is associated with.
projectId	string	true	The project the job belongs to.
status	string	true	The job status.
url	string	true	A URL that can be used to request details about the job.

Enumerated Values¶

Property Value

jobType [model, predict, trainingPredictions, featureImpact, featureEffects, shapImpact, anomalyAssessment, shapExplanations, shapMatrix, reasonCodesInitialization, reasonCodes, predictionExplanations, predictionExplanationsInitialization, primeDownloadValidation, ruleFitDownloadValidation, primeRulesets, primeModel, modelExport, usageData, modelXRay, accuracyOverTime, seriesAccuracy, validateRatingTable, generateComplianceDocumentation, automatedDocumentation, eda, pipeline, calculatePredictionIntervals, calculatePredictionIntervalBoundUsingOnlineConformal, batchVarTypeTransform, computeImageActivationMaps, computeImageAugmentations, computeImageEmbeddings, computeDocumentTextExtractionSamples, externalDatasetInsights, startDatetimePartitioning, runSegmentationTasks, piiDetection, computeBiasAndFairness, sensitivityTesting, clusterInsights, onnxExport, scoringCodeSegmentedModeling, insights, distributionPredictionModel, batchScoringAvailableForecastPoints, notebooksScheduling, uncategorized]

status [queue, inprogress, error, ABORTED, COMPLETED]

JobListResponse

{
  "count": 0,
  "jobs": [
    {
      "id": "string",
      "isBlocked": true,
      "jobType": "model",
      "message": "string",
      "modelId": "string",
      "projectId": "string",
      "status": "queue",
      "url": "string"
    }
  ],
  "next": "string",
  "previous": "string"
}

Properties¶

Name	Type	Required	Description
count	integer	true	the number of jobs returned.
jobs	[JobDetailsResponse]	true	A json array of jobs
next	string¦null	true	URL pointing to the next page (if null, there is no next page).
previous	string¦null	true	URL pointing to the previous page (if null, there is no previous page).

MultiseriesNamesControllerDataRecord

{
  "items": [
    "string"
  ]
}

Data fields of the multi series names

Properties¶

Name	Type	Required	Restrictions	Description
items	[string]	true		List of series names

MultiseriesNamesControllerResponse

{
  "count": 0,
  "data": {
    "items": [
      "string"
    ]
  },
  "next": "string",
  "previous": "string",
  "totalSeriesCount": 0
}

Properties¶

Name	Type	Required	Description
count	integer	true	Total number of series items in the response
data	MultiseriesNamesControllerDataRecord	true	Data fields of the multi series names
next	string¦null	true	A URL pointing to the next page (if `null`, there is no next page).
previous	string¦null	true	A URL pointing to the previous page (if `null`, there is no previous page).
totalSeriesCount	integer	true	Total number of series items

MultiseriesPayload

{
  "datetimePartitionColumn": "string",
  "multiseriesIdColumns": [
    "string"
  ]
}

Properties¶

Name	Type	Required	Restrictions	Description
datetimePartitionColumn	string	true		The date column that will be used to perform detection and validation for.
multiseriesIdColumns	[string]	false	minItems: 1	List of one or more names of potential multiseries id columns. If not provided, all numerical and categorical columns are used.

OAuthCredentials

{
  "credentialType": "oauth",
  "oauthAccessToken": null,
  "oauthClientId": null,
  "oauthClientSecret": null,
  "oauthRefreshToken": "string"
}

Properties¶

Name	Type	Required	Description
credentialType	string	true	The type of these credentials, 'oauth' here.
oauthAccessToken	string¦null	false	The oauth access token.
oauthClientId	string¦null	false	The oauth client ID.
oauthClientSecret	string¦null	false	The oauth client secret.
oauthRefreshToken	string	true	The oauth refresh token.

Enumerated Values¶

Property	Value
credentialType	`oauth`

OptimizedDatetimePartitioningData

{
  "aggregationType": "total",
  "allowPartialHistoryTimeSeriesPredictions": false,
  "autopilotClusterList": [
    2
  ],
  "autopilotDataSamplingMethod": "random",
  "autopilotDataSelectionMethod": "duration",
  "backtests": [
    {
      "gapDuration": "string",
      "index": 0,
      "validationDuration": "string",
      "validationStartDate": "2019-08-24T14:15:22Z"
    }
  ],
  "calendarId": "string",
  "clusteringBufferDisabled": false,
  "crossSeriesGroupByColumns": [
    "string"
  ],
  "datetimePartitionColumn": "string",
  "defaultToAPriori": true,
  "defaultToDoNotDerive": true,
  "defaultToKnownInAdvance": true,
  "differencingMethod": "auto",
  "disableHoldout": false,
  "featureDerivationWindowEnd": 0,
  "featureDerivationWindowStart": 0,
  "featureSettings": [
    {
      "aPriori": true,
      "doNotDerive": true,
      "featureName": "string",
      "knownInAdvance": true
    }
  ],
  "forecastWindowEnd": 0,
  "forecastWindowStart": 0,
  "gapDuration": "string",
  "holdoutDuration": "string",
  "holdoutEndDate": "2019-08-24T14:15:22Z",
  "holdoutStartDate": "2019-08-24T14:15:22Z",
  "isHoldoutModified": true,
  "modelSplits": 5,
  "multiseriesIdColumns": [
    "string"
  ],
  "numberOfBacktests": 1,
  "periodicities": [
    {
      "timeSteps": 0,
      "timeUnit": "MILLISECOND"
    }
  ],
  "target": "string",
  "treatAsExponential": "auto",
  "unsupervisedMode": false,
  "unsupervisedType": "anomaly",
  "useCrossSeriesFeatures": false,
  "useSupervisedFeatureReduction": true,
  "useTimeSeries": false,
  "validationDuration": "string",
  "windowsBasisUnit": "MILLISECOND"
}

Properties¶

Name	Type	Required	Restrictions	Description
aggregationType	string	false		For multiseries projects only. The aggregation type to apply when creating cross-series features.
allowPartialHistoryTimeSeriesPredictions	boolean	false		Specifies whether the time series predictions can use partial historical data.
autopilotClusterList	[integer]¦null	false	maxItems: 10	A list of integers where each value will be used as the number of clusters in Autopilot model(s) for unsupervised clustering projects. Cannot be specified unless `unsupervisedMode` is true and `unsupervisedType` is set to `clustering`.
autopilotDataSamplingMethod	string	false		Defines how autopilot will select subsample from training dataset in OTV/TS projects. Defaults to 'latest' for 'rowCount' dataSelectionMethod and to 'random' for 'duration'.
autopilotDataSelectionMethod	string	false		The Data Selection method to be used by autopilot when creating models for datetime-partitioned datasets.
backtests	[oneOf]	false	maxItems: 20 minItems: 1	An array specifying individual backtests.

oneOf

Name	Type	Required	Restrictions	Description
» anonymous	BacktestOldMethodForOpenApi	false		Method 1 - pass validation and gap durations

xor

Name	Type	Required	Restrictions	Description
» anonymous	BacktestNewMethodForOpenApi	false		Method 2 - directly configure the start and end dates of each partition, including the training partition.

continued

Name	Type	Required	Restrictions	Description
calendarId	string	false		The ID of the calendar to be used in this project.
clusteringBufferDisabled	boolean	false		A boolean value indicating whether an clustering buffer creation should be disabled for unsupervised time series clustering project.
crossSeriesGroupByColumns	[string]	false	maxItems: 1	For multiseries projects with cross-series features enabled only. List of columns (currently of length 1). Setting that indicates how to further split series into related groups. For example, if every series is sales of an individual product, the series group-by could be the product category with values like "men's clothing", "sports equipment", etc.
datetimePartitionColumn	string	true		The date column that will be used as a datetime partition column.
defaultToAPriori	boolean	false		Renamed to `defaultToKnownInAdvance`.
defaultToDoNotDerive	boolean	false		For time series projects only. Sets whether all features default to being treated as do-not-derive features, excluding them from feature derivation. Individual features can be set to a value different than the default by using the `featureSettings` parameter.
defaultToKnownInAdvance	boolean	false		For time series projects only. Sets whether all features default to being treated as known in advance features, which are features that are known into the future. Features marked as known in advance must be specified into the future when making predictions. The default is false, all features are not known in advance. Individual features can be set to a value different than the default using the `featureSettings` parameter. See the :ref:`Time Series Overview <time_series_overview>` for more context.
differencingMethod	string	false		For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems `simple` and `seasonal` are not allowed. Parameter `periodicities` must be specified if `seasonal` is chosen. Defaults to `auto`.
disableHoldout	boolean	false		Whether to suppress allocating a holdout fold. If `disableHoldout` is set to true, `holdoutStartDate` and `holdoutDuration` must not be set.
featureDerivationWindowEnd	integer	false	maximum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the past relative to the forecast point the feature derivation window should end.
featureDerivationWindowStart	integer	false	maximum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the past relative to the forecast point the feature derivation window should begin.
featureSettings	[FeatureSetting]	false		An array specifying per feature settings. Features can be left unspecified.
forecastWindowEnd	integer	false	minimum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the future relative to the forecast point the forecast window should end.
forecastWindowStart	integer	false	minimum: 0	For time series projects only. How many timeUnits of the datetimePartitionColumn into the future relative to the forecast point the forecast window should start.
gapDuration	string(duration)	false		The duration of the gap between holdout training and holdout scoring data. For time series projects, defaults to the duration of the gap between the end of the feature derivation window and the beginning of the forecast window. For OTV projects, defaults to a zero duration (P0Y0M0D).
holdoutDuration	string(duration)	false		The duration of holdout scoring data. When specifying `holdoutDuration`, `holdoutStartDate` must also be specified. This attribute cannot be specified when `disableHoldout` is true.
holdoutEndDate	string(date-time)	false		The end date of holdout scoring data. When specifying `holdoutEndDate`, `holdoutStartDate` must also be specified. This attribute cannot be specified when `disableHoldout` is true.
holdoutStartDate	string(date-time)	false		The start date of holdout scoring data. When specifying `holdoutStartDate`, one of `holdoutEndDate` or `holdoutDuration` must also be specified. This attribute cannot be specified when `disableHoldout` is true.
isHoldoutModified	boolean	false		A boolean value indicating whether holdout settings (start/end dates) have been modified by user.
modelSplits	integer	false	maximum: 10 minimum: 1	Sets the cap on the number of jobs per model used when building models to control number of jobs in the queue. Higher number of modelSplits will allow for less downsampling leading to the use of more post-processed data.
multiseriesIdColumns	[string]	false	minItems: 1	May be used only with time series projects. An array of the column names identifying the series to which each row of the dataset belongs. Currently only one multiseries ID column is supported. See the :ref:`multiseries <multiseries>` section of the time series documentation for more context.
numberOfBacktests	integer	false	maximum: 20 minimum: 1	The number of backtests to use. If omitted, defaults to a positive value selected by the server based on the validation and gap durations.
periodicities	[Periodicity]	false		A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing_method' will default to 'seasonal' if not provided or 'auto'.
target	string	false		Name of the target column.
treatAsExponential	string	false		For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems `always` is not allowed. Defaults to `auto`.
unsupervisedMode	boolean	false		A boolean value indicating whether an unsupervised project should be created.
unsupervisedType	string¦null	false		The type of unsupervised project. Only valid when `unsupervisedMode` is true. If `unsupervisedMode`, defaults to `anomaly`.
useCrossSeriesFeatures	boolean	false		For multiseries projects only. Indicating whether to use cross-series features.
useSupervisedFeatureReduction	boolean	false		When true, during feature generation DataRobot runs a supervised algorithm that identifies those features with predictive impact on the target and builds feature lists using only qualifying features. Setting false can severely impact autopilot duration, especially for datasets with many features.
useTimeSeries	boolean	false		A boolean value indicating whether a time series project should be created instead of a regular project which uses datetime partitioning.
validationDuration	string(duration)	false		The default validation duration for all backtests. If the primary date/time feature in a time series project is irregular, you cannot set a default validation length. Instead, set each duration individually. For an OTV project setting the validation duration will always use regular partitioning. Omitting it will use irregular partitioning if the date/time feature is irregular.
windowsBasisUnit	string	false		For time series projects only. Indicates which unit is basis for feature derivation window and forecast window. Valid options are detected time unit or `ROW`. If omitted, the default value is detected time unit.

Enumerated Values¶

Property	Value
aggregationType	[`total`, `average`]
autopilotDataSamplingMethod	[`random`, `latest`]
autopilotDataSelectionMethod	[`duration`, `rowCount`]
differencingMethod	[`auto`, `none`, `simple`, `seasonal`]
treatAsExponential	[`auto`, `never`, `always`]
unsupervisedType	[`anomaly`, `clustering`]
windowsBasisUnit	[`MILLISECOND`, `SECOND`, `MINUTE`, `HOUR`, `DAY`, `WEEK`, `MONTH`, `QUARTER`, `YEAR`, `ROW`]

OptimizedDatetimePartitioningList

{
  "datetimePartitionColumn": "string",
  "id": "string",
  "partitionData": {
    "aggregationType": "total",
    "allowPartialHistoryTimeSeriesPredictions": true,
    "autopilotDataSamplingMethod": "random",
    "autopilotDataSelectionMethod": "duration",
    "availableHoldoutEndDate": "2019-08-24T14:15:22Z",
    "availableTrainingDuration": "string",
    "availableTrainingEndDate": "2019-08-24T14:15:22Z",
    "availableTrainingStartDate": "2019-08-24T14:15:22Z",
    "backtests": [
      {
        "availableTrainingDuration": "string",
        "availableTrainingEndDate": "2019-08-24T14:15:22Z",
        "availableTrainingStartDate": "2019-08-24T14:15:22Z",
        "gapDuration": "string",
        "gapEndDate": "2019-08-24T14:15:22Z",
        "gapStartDate": "2019-08-24T14:15:22Z",
        "index": 0,
        "primaryTrainingDuration": "string",
        "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
        "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
        "validationDuration": "string",
        "validationEndDate": "2019-08-24T14:15:22Z",
        "validationStartDate": "2019-08-24T14:15:22Z"
      }
    ],
    "calendarId": "string",
    "calendarName": "string",
    "clusteringBufferDisabled": false,
    "crossSeriesGroupByColumns": [
      "string"
    ],
    "dateFormat": "string",
    "datetimePartitionColumn": "string",
    "datetimePartitioningId": "string",
    "defaultToAPriori": true,
    "defaultToDoNotDerive": true,
    "defaultToKnownInAdvance": true,
    "differencingMethod": "auto",
    "disableHoldout": true,
    "featureDerivationWindowEnd": 0,
    "featureDerivationWindowStart": 0,
    "featureSettings": [
      {
        "aPriori": true,
        "doNotDerive": true,
        "featureName": "string",
        "knownInAdvance": true
      }
    ],
    "forecastWindowEnd": 0,
    "forecastWindowStart": 0,
    "gapDuration": "string",
    "gapEndDate": "2019-08-24T14:15:22Z",
    "gapStartDate": "2019-08-24T14:15:22Z",
    "holdoutDuration": "string",
    "holdoutEndDate": "2019-08-24T14:15:22Z",
    "holdoutStartDate": "2019-08-24T14:15:22Z",
    "isHoldoutModified": true,
    "modelSplits": 1,
    "multiseriesIdColumns": [
      "string"
    ],
    "numberOfBacktests": 1,
    "numberOfDoNotDeriveFeatures": 0,
    "numberOfKnownInAdvanceFeatures": 0,
    "partitioningExtendedWarnings": [
      {
        "backtestIndex": 0,
        "partition": "string",
        "warnings": [
          {
            "message": "string",
            "title": "string",
            "type": "string"
          }
        ]
      }
    ],
    "partitioningWarnings": [
      {
        "backtestIndex": 0,
        "partition": "string",
        "warnings": [
          "string"
        ]
      }
    ],
    "periodicities": [
      {
        "timeSteps": 0,
        "timeUnit": "MILLISECOND"
      }
    ],
    "primaryTrainingDuration": "string",
    "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
    "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
    "projectId": "string",
    "treatAsExponential": "auto",
    "unsupervisedMode": true,
    "unsupervisedType": "anomaly",
    "useCrossSeriesFeatures": true,
    "useTimeSeries": true,
    "validationDuration": "string",
    "windowsBasisUnit": "MILLISECOND"
  },
  "target": "string"
}

Properties¶

Name	Type	Required	Description
datetimePartitionColumn	string	true	The date column that will be used as a datetime partition column.
id	string	true	The ID of the datetime partitioning.
partitionData	DatetimePartitioningResponse	true	none
target	string	true	The name of the target column.

OptimizedDatetimePartitioningListResponse

{
  "count": 0,
  "data": [
    {
      "datetimePartitionColumn": "string",
      "id": "string",
      "partitionData": {
        "aggregationType": "total",
        "allowPartialHistoryTimeSeriesPredictions": true,
        "autopilotDataSamplingMethod": "random",
        "autopilotDataSelectionMethod": "duration",
        "availableHoldoutEndDate": "2019-08-24T14:15:22Z",
        "availableTrainingDuration": "string",
        "availableTrainingEndDate": "2019-08-24T14:15:22Z",
        "availableTrainingStartDate": "2019-08-24T14:15:22Z",
        "backtests": [
          {
            "availableTrainingDuration": "string",
            "availableTrainingEndDate": "2019-08-24T14:15:22Z",
            "availableTrainingStartDate": "2019-08-24T14:15:22Z",
            "gapDuration": "string",
            "gapEndDate": "2019-08-24T14:15:22Z",
            "gapStartDate": "2019-08-24T14:15:22Z",
            "index": 0,
            "primaryTrainingDuration": "string",
            "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
            "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
            "validationDuration": "string",
            "validationEndDate": "2019-08-24T14:15:22Z",
            "validationStartDate": "2019-08-24T14:15:22Z"
          }
        ],
        "calendarId": "string",
        "calendarName": "string",
        "clusteringBufferDisabled": false,
        "crossSeriesGroupByColumns": [
          "string"
        ],
        "dateFormat": "string",
        "datetimePartitionColumn": "string",
        "datetimePartitioningId": "string",
        "defaultToAPriori": true,
        "defaultToDoNotDerive": true,
        "defaultToKnownInAdvance": true,
        "differencingMethod": "auto",
        "disableHoldout": true,
        "featureDerivationWindowEnd": 0,
        "featureDerivationWindowStart": 0,
        "featureSettings": [
          {
            "aPriori": true,
            "doNotDerive": true,
            "featureName": "string",
            "knownInAdvance": true
          }
        ],
        "forecastWindowEnd": 0,
        "forecastWindowStart": 0,
        "gapDuration": "string",
        "gapEndDate": "2019-08-24T14:15:22Z",
        "gapStartDate": "2019-08-24T14:15:22Z",
        "holdoutDuration": "string",
        "holdoutEndDate": "2019-08-24T14:15:22Z",
        "holdoutStartDate": "2019-08-24T14:15:22Z",
        "isHoldoutModified": true,
        "modelSplits": 1,
        "multiseriesIdColumns": [
          "string"
        ],
        "numberOfBacktests": 1,
        "numberOfDoNotDeriveFeatures": 0,
        "numberOfKnownInAdvanceFeatures": 0,
        "partitioningExtendedWarnings": [
          {
            "backtestIndex": 0,
            "partition": "string",
            "warnings": [
              {
                "message": "string",
                "title": "string",
                "type": "string"
              }
            ]
          }
        ],
        "partitioningWarnings": [
          {
            "backtestIndex": 0,
            "partition": "string",
            "warnings": [
              "string"
            ]
          }
        ],
        "periodicities": [
          {
            "timeSteps": 0,
            "timeUnit": "MILLISECOND"
          }
        ],
        "primaryTrainingDuration": "string",
        "primaryTrainingEndDate": "2019-08-24T14:15:22Z",
        "primaryTrainingStartDate": "2019-08-24T14:15:22Z",
        "projectId": "string",
        "treatAsExponential": "auto",
        "unsupervisedMode": true,
        "unsupervisedType": "anomaly",
        "useCrossSeriesFeatures": true,
        "useTimeSeries": true,
        "validationDuration": "string",
        "windowsBasisUnit": "MILLISECOND"
      },
      "target": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Properties¶

Name	Type	Required	Description
count	integer	false	Number of items returned on this page.
data	[OptimizedDatetimePartitioningList]	true	A list of datetime partitionings returned in order of creation.
next	string(uri)¦null	true	URL pointing to the next page (if null, there is no next page).
previous	string(uri)¦null	true	URL pointing to the previous page (if null, there is no previous page).

Partition

{
  "cvHoldoutLevel": "string",
  "cvMethod": "random",
  "datetimeCol": "string",
  "datetimePartitionColumn": "string",
  "holdoutLevel": "string",
  "holdoutPct": 0,
  "partitionKeyCols": [
    "string"
  ],
  "reps": 0,
  "trainingLevel": "string",
  "useTimeSeries": true,
  "userPartitionCol": "string",
  "validationLevel": "string",
  "validationPct": 0,
  "validationType": "CV"
}

The partition object of a project indicates the settings used for partitioning. Depending on the partitioning selected, many of the options will be null.

Properties¶

Name	Type	Required	Description
cvHoldoutLevel	string¦null	true	If a user partition column was used with cross validation, the value assigned to the holdout set
cvMethod	string	true	The partitioning method used. Note that "date" partitioning is an old partitioning method no longer supported for new projects, as of API version v2.0.
datetimeCol	string¦null	true	If a date partition column was used, the name of the column. Note that datetimeCol applies to an old partitioning method no longer supported for new projects, as of API version v2.0.
datetimePartitionColumn	string¦null	false	If a datetime partition column was used, the name of the column.
holdoutLevel	string¦null	true	If a user partition column was used with train-validation-holdout split, the value assigned to the holdout set.
holdoutPct	number¦null	true	The percentage of the dataset reserved for the holdout set.
partitionKeyCols	[string]¦null	true	An array containing a single string - the name of the group partition column
reps	integer¦null	true	If cross validation was used, the number of folds to use.
trainingLevel	string¦null	true	If a user partition column was used with train-validation-holdout split, the value assigned to the training set.
useTimeSeries	boolean¦null	false	Indicates whether a time series project was created as opposed to a regular project using datetime partitioning.
userPartitionCol	string¦null	true	If a user partition column was used, the name of the column.
validationLevel	string¦null	true	If a user partition column was used with train-validation-holdout split, the value assigned to the validation set.
validationPct	number¦null	true	If train-validation-holdout split was used, the percentage of the dataset used for the validation set.
validationType	string	true	The type of validation used. Either CV (cross validation) or TVH (train-validation-holdout split).

Enumerated Values¶

Property	Value
cvMethod	[`random`, `stratified`, `datetime`, `user`, `group`, `date`]
validationType	[`CV`, `TVH`]

PartitioningExtendedWarning

{
  "backtestIndex": 0,
  "partition": "string",
  "warnings": [
    {
      "message": "string",
      "title": "string",
      "type": "string"
    }
  ]
}

Properties¶

Name	Type	Required	Description
backtestIndex	integer¦null	true	Backtest index. Null if the warning does not correspond to a single backtest.
partition	string	true	Partition name.
warnings	[PartitioningSingleExtendedWarning]	true	A list of strings representing warnings for the specified partition

PartitioningSingleExtendedWarning

{
  "message": "string",
  "title": "string",
  "type": "string"
}

Properties¶

Name	Type	Required	Description
message	string	true	Warning message.
title	string	true	Warning short title.
type	string	true	Warning severity type.

PartitioningWarning

{
  "backtestIndex": 0,
  "partition": "string",
  "warnings": [
    "string"
  ]
}

Properties¶

Name	Type	Required	Description
backtestIndex	integer¦null	true	Backtest index. Null if the warning does not correspond to a single backtest.
partition	string	true	Partition name.
warnings	[string]	true	A list of strings representing warnings for the specified partition

PasswordCredentials

{
  "catalogVersionId": "string",
  "password": "string",
  "url": "string",
  "user": "string"
}

Properties¶

Name	Type	Required	Description
catalogVersionId	string	false	The ID of the latest version of the catalog entry.
password	string	true	The password (in cleartext) for database authentication. The password will be encrypted on the server side in scope of HTTP request and never saved or stored.
url	string	false	The link to retrieve more detailed information about the entity that uses this catalog dataset.
user	string	true	The username for database authentication.

Periodicity

{
  "timeSteps": 0,
  "timeUnit": "MILLISECOND"
}

Properties¶

Name	Type	Required	Restrictions	Description
timeSteps	integer	true	minimum: 0	The number of time steps.
timeUnit	string	true		The time unit or `ROW` if windowsBasisUnit is `ROW`

Enumerated Values¶

Property	Value
timeUnit	[`MILLISECOND`, `SECOND`, `MINUTE`, `HOUR`, `DAY`, `WEEK`, `MONTH`, `QUARTER`, `YEAR`, `ROW`]

ProjectAdvancedOptionsResponse

{
  "allowedPairwiseInteractionGroups": [
    [
      "string"
    ]
  ],
  "blendBestModels": true,
  "blueprintThreshold": 0,
  "considerBlendersInRecommendation": true,
  "defaultMonotonicDecreasingFeaturelistId": "string",
  "defaultMonotonicIncreasingFeaturelistId": "string",
  "downsampledMajorityRows": 0,
  "downsampledMinorityRows": 0,
  "eventsCount": "string",
  "exposure": "string",
  "majorityDownsamplingRate": 0,
  "minSecondaryValidationModelCount": true,
  "offset": [
    "string"
  ],
  "onlyIncludeMonotonicBlueprints": false,
  "prepareModelForDeployment": true,
  "responseCap": true,
  "runLeakageRemovedFeatureList": true,
  "scoringCodeOnly": true,
  "seed": "string",
  "shapOnlyMode": true,
  "smartDownsampled": true,
  "weights": "string"
}

Information related to the current model of the deployment.

Properties¶

Name	Type	Required	Description
allowedPairwiseInteractionGroups	[array]	false	For GAM models - specify groups of columns for which pairwise interactions will be allowed. E.g. if set to [["A", "B", "C"], ["C", "D"]] then GAM models will allow interactions between columns AxB, BxC, AxC, CxD. All others (AxD, BxD) will not be considered. If not specified - all possible interactions will be considered by model.
blendBestModels	boolean	true	blend best models during Autopilot run [DEPRECATED]
blueprintThreshold	integer¦null	true	an upper bound on running time (in hours), such that models exceeding the bound will be excluded in subsequent autopilot runs
considerBlendersInRecommendation	boolean	false	Include blenders when selecting a model to prepare for deployment in an Autopilot Run.[DEPRECATED]
defaultMonotonicDecreasingFeaturelistId	string¦null	true	null or str, the ID of the featurelist specifying a set of features with a monotonically decreasing relationship to the target. All blueprints generated in the project use this as their default monotonic constraint, but it can be overriden at model submission time.
defaultMonotonicIncreasingFeaturelistId	string¦null	true	null or str, the ID of the featurelist specifying a set of features with a monotonically increasing relationship to the target. All blueprints generated in the project use this as their default monotonic constraint, but it can be overriden at model submission time.
downsampledMajorityRows	integer¦null	true	the total number of the majority rows available for modeling, or null for projects without smart downsampling
downsampledMinorityRows	integer¦null	true	the total number of the minority rows available for modeling, or null for projects without smart downsampling
eventsCount	string¦null	false	the name of the event count column, if specified, otherwise null.
exposure	string¦null	false	the name of the exposure column, if specified.
majorityDownsamplingRate	number¦null	true	the percentage between 0 and 100 of the majority rows that are kept, or null for projects without smart downsampling
minSecondaryValidationModelCount	boolean	false	Compute "All backtest" scores (datetime models) or cross validation scores for the specified number of highest ranking models on the Leaderboard, if over the Autopilot default.
offset	[string]¦null	false	the list of names of the offset columns, if specified, otherwise null.
onlyIncludeMonotonicBlueprints	boolean	true	whether the project only includes blueprints support enforcing monotonic constraints
prepareModelForDeployment	boolean¦null	true	Prepare model for deployment during Autopilot run. The preparation includes creating reduced feature list models, retraining best model on higher sample size, computing insights and assigning "RECOMMENDED FOR DEPLOYMENT" label.
responseCap	any	true	defaults to False, if specified used to cap the maximum response of a model

oneOf

Name	Type	Required	Restrictions	Description
» anonymous	boolean	false		none

xor

Name	Type	Required	Restrictions	Description
» anonymous	number	false	maximum: 1 minimum: 0.5	none

continued

Name	Type	Required	Description
runLeakageRemovedFeatureList	boolean	false	Run Autopilot on Leakage Removed feature list (if exists).
scoringCodeOnly	boolean	false	Keep only models that can be converted to scorable java code during Autopilot run.
seed	string¦null	true	defaults to null, the random seed to be used if specified
shapOnlyMode	boolean¦null	true	Keep only models that support SHAP values during Autopilot run. Use SHAP-based insights wherever possible. For pre SHAP-only mode projects this is always `null`.
smartDownsampled	boolean	true	whether the project uses smart downsampling to throw away excess rows of the majority class. Smart downsampled projects express all sample percents in terms of percent of minority rows (as opposed to percent of all rows).
weights	string¦null	true	the name of the weight column, if specified, otherwise null.

ProjectClone

{
  "copyOptions": false,
  "projectId": "string",
  "projectName": "string"
}

Properties¶

Name	Type	Required	Description
copyOptions	boolean	false	Whether all project options should be copied to the cloned project.
projectId	string	true	The ID of the project to clone.
projectName	string	false	The name of the project to be created.

ProjectCreate

{
  "credentialData": {
    "credentialType": "basic",
    "password": "string",
    "user": "string"
  },
  "credentialId": "string",
  "dataSourceId": "string",
  "datasetId": "string",
  "datasetVersionId": "string",
  "password": "string",
  "projectName": "string",
  "recipeId": "string",
  "url": "string",
  "useKerberos": true,
  "user": "string"
}

Properties¶

Name	Type	Required	Restrictions	Description
credentialData	any	false		The credentials to authenticate with the database, to be used instead of credential ID. Can only be used along with datasetId or dataSourceId.

oneOf

Name	Type	Required	Restrictions	Description
» anonymous	BasicCredentials	false		none

xor

Name	Type	Required	Restrictions	Description
» anonymous	S3Credentials	false		none

xor

Name	Type	Required	Restrictions	Description
» anonymous	OAuthCredentials	false		none

xor

Name	Type	Required	Restrictions	Description
» anonymous	SnowflakeKeyPairCredentials	false		none

xor

Name	Type	Required	Restrictions	Description
» anonymous	GoogleServiceAccountCredentials	false		none

xor

Name	Type	Required	Restrictions	Description
» anonymous	DatabricksAccessTokenCredentials	false		none

xor

Name	Type	Required	Restrictions	Description
» anonymous	DatabricksServicePrincipalCredentials	false		none

xor

Name	Type	Required	Restrictions	Description
» anonymous	AzureServicePrincipalCredentials	false		none

continued

Name	Type	Required	Description
credentialId	string	false	The ID of the set of credentials to authenticate with the database. Can only be used along with datasetId or dataSourceId.
dataSourceId	string	false	Identifier for the data source to retrieve.
datasetId	string	false	The ID of the dataset entry to use for the project dataset.
datasetVersionId	string	false	Only used when also providing a datasetId, and specifies the the ID of the dataset version to use for the project dataset. If not specified, the latest version associated with the dataset ID is used.
password	string	false	The password (in cleartext) for database authentication. The password will be encrypted on the server side as part of the HTTP request and never saved or stored. Can only be used along with datasetId or dataSourceId. DEPRECATED: please use credentialId or credentialData instead.
projectName	string	false	The name of the project to be created. If not specified, 'Untitled Project' will be used for database connections and file name will be used as the project name.
recipeId	string	false	The ID of the wrangling recipe that will be used for project creation.
url	string(url)	false	The URL to download the dataset used to create the project.
useKerberos	boolean	false	If true, use Kerberos authentication for database authentication. Default is false. Can only be used along with datasetId or dataSourceId.
user	string	false	The username for database authentication. Can only be used along with datasetId or dataSourceId. DEPRECATED: please use credentialId or credentialData instead.

ProjectCreateResponse

{
  "pid": "string"
}

Properties¶

Name	Type	Required	Restrictions	Description
pid	string	true		The project ID.

ProjectDetailsResponse

{
  "advancedOptions": {
    "allowedPairwiseInteractionGroups": [
      [
        "string"
      ]
    ],
    "blendBestModels": true,
    "blueprintThreshold": 0,
    "considerBlendersInRecommendation": true,
    "defaultMonotonicDecreasingFeaturelistId": "string",
    "defaultMonotonicIncreasingFeaturelistId": "string",
    "downsampledMajorityRows": 0,
    "downsampledMinorityRows": 0,
    "eventsCount": "string",
    "exposure": "string",
    "majorityDownsamplingRate": 0,
    "minSecondaryValidationModelCount": true,
    "offset": [
      "string"
    ],
    "onlyIncludeMonotonicBlueprints": false,
    "prepareModelForDeployment": true,
    "responseCap": true,
    "runLeakageRemovedFeatureList": true,
    "scoringCodeOnly": true,
    "seed": "string",
    "shapOnlyMode": true,
    "smartDownsampled": true,
    "weights": "string"
  },
  "autopilotClusterList": [
    2
  ],
  "autopilotMode": 0,
  "created": "2019-08-24T14:15:22Z",
  "featureEngineeringPredictionPoint": "string",
  "fileName": "string",
  "holdoutUnlocked": true,
  "id": "string",
  "maxClusters": 2,
  "maxTrainPct": 0,
  "maxTrainRows": 0,
  "metric": "string",
  "minClusters": 2,
  "partition": {
    "cvHoldoutLevel": "string",
    "cvMethod": "random",
    "datetimeCol": "string",
    "datetimePartitionColumn": "string",
    "holdoutLevel": "string",
    "holdoutPct": 0,
    "partitionKeyCols": [
      "string"
    ],
    "reps": 0,
    "trainingLevel": "string",
    "useTimeSeries": true,
    "userPartitionCol": "string",
    "validationLevel": "string",
    "validationPct": 0,
    "validationType": "CV"
  },
  "positiveClass": 0,
  "projectName": "string",
  "stage": "string",
  "target": "string",
  "targetType": "Binary",
  "unsupervisedMode": true,
  "unsupervisedType": "anomaly",
  "useFeatureDiscovery": true
}

Properties¶

Name	Type	Required	Restrictions	Description
advancedOptions	ProjectAdvancedOptionsResponse	true		Information related to the current model of the deployment.
autopilotClusterList	[integer]¦null	false	maxItems: 10	Optional. A list of integers where each value will be used as the number of clusters in Autopilot model(s) for unsupervised clustering projects. Cannot be specified unless unsupervisedMode is true and unsupervisedType is set to 'clustering'.
autopilotMode	integer	true		The current autopilot mode, 0 for full autopilot, 2 for manual mode, 3 for quick mode, 4 for comprehensive mode
created	string(date-time)	true		The time of project creation.
featureEngineeringPredictionPoint	string¦null	false		The date column to be used as the prediction point for time-based feature engineering.
fileName	string	true		The name of the dataset used to create the project.
holdoutUnlocked	boolean	true		whether the holdout has been unlocked
id	string	true		The ID of a project.
maxClusters	integer¦null	false	maximum: 100 minimum: 2	Only valid when unsupervisedMode is True and unsupervisedType is 'clustering'. The maximum number of clusters allowed when training clustering models. If specified cannot be exceed the number of rows in a project's dataset divided by 50 and must be less than or equal to `minClusters`. If unsupervisedMode is True and unsupervisedType is 'clustering' then defaults to the number of rows in the project's dataset divided by 50 or 100 if that number of greater than 100.
maxTrainPct	number	true		the maximum percentage of the dataset that can be used to successfully train a model without going into the validation data.
maxTrainRows	integer	true		the maximum number of rows of the dataset that can be used to successfully train a model without going into the validation data
metric	string	true		the metric used to select the best-performing models.
minClusters	integer¦null	false	maximum: 100 minimum: 2	Only valid when unsupervisedMode is True and unsupervisedType is 'clustering'. The minimum number of clusters allowed when training clustering models. If specified cannot be exceed the number of rows in a project's dataset divided by 50 and must be less than or equal to `maxClusters`. If unsupervisedMode is True and unsupervisedType is 'clustering' then defaults to 2.
partition	ProjectPartitionResponse	true		The partition object of a project indicates the settings used for partitioning. Depending on the partitioning selected, many of the options will be null. Note that for projects whose `cvMethod` is `"datetime"`, full specification of the partitioning method can be found at GET /api/v2/projects/{projectId}/datetimePartitioning/.
positiveClass	number¦null	true		if the project uses binary classification, the class designated to be the positive class. Otherwise, null.
projectName	string	true		The name of a project.
stage	string	true		the stage of the project - if modeling, then the target is successfully set, and modeling or predictions can proceed.
target	string	true		the target of the project, null if project is unsupervised.
targetType	string¦null	true		The target type of the project.
unsupervisedMode	boolean	true		indicates whether a project is unsupervised.
unsupervisedType	string¦null	false		Only valid when unsupervisedMode is True. The type of unsupervised project, anomaly or clustering. If unsupervisedMode, defaults to 'anomaly'.
useFeatureDiscovery	boolean	true		A boolean value indicating whether a feature discovery project was created as opposed to a regular project.

Enumerated Values¶

Property	Value
targetType	[`Binary`, `Regression`, `Multiclass`, `minInflated`, `Multilabel`, `TextGeneration`, `GeoPoint`]
unsupervisedType	[`anomaly`, `clustering`]

ProjectNuke

{
  "creator": "string",
  "deletedAfter": "2019-08-24T14:15:22Z",
  "deletedBefore": "2019-08-24T14:15:22Z",
  "limit": 1000,
  "offset": 0,
  "organization": "string",
  "projectIds": [
    "string"
  ],
  "searchFor": "string"
}

Properties¶

Name	Type	Required	Restrictions	Description
creator	string	false		Creator ID to filter projects by
deletedAfter	string(date-time)	false		ISO-8601 formatted date projects were deleted after
deletedBefore	string(date-time)	false		ISO-8601 formatted date projects were deleted before
limit	integer	false	maximum: 1000 minimum: 1	At most this many projects are deleted.
offset	integer	false	minimum: 0	This many projects will be skipped.
organization	string	false		ID of organization that projects should belong to
projectIds	[string]	false	maxItems: 1000 minItems: 1	List of project IDs to delete permanently.
searchFor	string	false		Project or dataset name to filter by

ProjectNukeJobListStatus

{
  "jobs": [
    {
      "created": "2019-08-24T14:15:22Z",
      "data": [
        {
          "message": "string",
          "projectId": "string",
          "status": "ABORTED"
        }
      ],
      "message": "string",
      "status": "ABORTED",
      "statusId": "string"
    }
  ]
}

Properties¶

Name	Type	Required	Restrictions	Description
jobs	[ProjectNukeJobStatus]	true		List of active permadelete jobs with their statuses.

ProjectNukeJobStatus

{
  "created": "2019-08-24T14:15:22Z",
  "data": [
    {
      "message": "string",
      "projectId": "string",
      "status": "ABORTED"
    }
  ],
  "message": "string",
  "status": "ABORTED",
  "statusId": "string"
}

Properties¶

Name	Type	Required	Restrictions	Description
created	string(date-time)	true		The time the status record was created.
data	[ProjectPermadeleteStatus]	true	maxItems: 1000 minItems: 1	List of projects and associated statuses.
message	string¦null	true		May contain further information about the status.
status	string	true		The processing state of the cleanup job.
statusId	string	true		The ID of the status object.

Enumerated Values¶

Property	Value
status	[`ABORTED`, `BLOCKED`, `COMPLETED`, `CREATED`, `ERROR`, `EXPIRED`, `INCOMPLETE`, `INITIALIZED`, `PAUSED`, `RUNNING`]

ProjectNukeJobStatusSummary

{
  "jobId": "string",
  "summary": {
    "aborted": 0,
    "completed": 0,
    "error": 0,
    "expired": 0
  }
}

Properties¶

Name	Type	Required	Restrictions	Description
jobId	string	true		The ID of the permadeletion multi-job.
summary	ProjectNukeJobStatusSummaryObject	true		Project permanent deletion status to count mapping.

ProjectNukeJobStatusSummaryObject

{
  "aborted": 0,
  "completed": 0,
  "error": 0,
  "expired": 0
}

Project permanent deletion status to count mapping.

Properties¶

Name	Type	Required	Restrictions	Description
aborted	integer	true	minimum: 0	Number of project permadelete jobs with Aborted status.
completed	integer	true	minimum: 0	Number of project permadelete jobs with Completed status.
error	integer	true	minimum: 0	Number of project permadelete jobs with Error status.
expired	integer	true	minimum: 0	Number of project permadelete jobs with Expired status.

ProjectPartitionResponse

{
  "cvHoldoutLevel": "string",
  "cvMethod": "random",
  "datetimeCol": "string",
  "datetimePartitionColumn": "string",
  "holdoutLevel": "string",
  "holdoutPct": 0,
  "partitionKeyCols": [
    "string"
  ],
  "reps": 0,
  "trainingLevel": "string",
  "useTimeSeries": true,
  "userPartitionCol": "string",
  "validationLevel": "string",
  "validationPct": 0,
  "validationType": "CV"
}

The partition object of a project indicates the settings used for partitioning. Depending on the partitioning selected, many of the options will be null. Note that for projects whose cvMethod is "datetime", full specification of the partitioning method can be found at GET /api/v2/projects/{projectId}/datetimePartitioning/.

Properties¶

Name	Type	Required	Restrictions	Description
cvHoldoutLevel	any	true		if a user partition column was used with cross validation, the value assigned to the holdout set

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	number	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	integer	false		none

continued

Name	Type	Required	Description
cvMethod	string	true	the partitioning method used. Note that "date" partitioning is an old partitioning method no longer supported for new projects, as of API version v2.0.
datetimeCol	string¦null	true	if a date partition column was used, the name of the column. Note that datetimeCol applies to an old partitioning method no longer supported for new projects, as of API version v2.0.
datetimePartitionColumn	string	false	if a datetime partition column was used, the name of the column
holdoutLevel	any	true	if a user partition column was used with train-validation-holdout split, the value assigned to the holdout set

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	number	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	integer	false		none

continued

Name	Type	Required	Description
holdoutPct	number	true	the percentage of the dataset reserved for the holdout set
partitionKeyCols	[string]¦null	true	An array containing a single string - the name of the group partition column
reps	number¦null	true	if cross validation was used, the number of folds to use
trainingLevel	any	true	if a user partition column was used with train-validation-holdout split, the value assigned to the training set

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	number	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	integer	false		none

continued

Name	Type	Required	Description
useTimeSeries	boolean¦null	true	A boolean value indicating whether a time series project was created as opposed to a regular project using datetime partitioning.
userPartitionCol	string¦null	true	if a user partition column was used, the name of the column
validationLevel	any	true	if a user partition column was used with train-validation-holdout split, the value assigned to the validation set

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	number	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	integer	false		none

continued

Name	Type	Required	Restrictions	Description
validationPct	number¦null	true		if train-validation-holdout split was used, the percentage of the dataset used for the validation set
validationType	string	true		either CV for cross-validation or TVH for train-validation-holdout split

Enumerated Values¶

Property	Value
cvMethod	[`random`, `user`, `stratified`, `group`, `datetime`]
validationType	[`CV`, `TVH`]

ProjectPermadeleteStatus

{
  "message": "string",
  "projectId": "string",
  "status": "ABORTED"
}

Properties¶

Name	Type	Required	Description
message	string¦null	true	May contain further information about the status.
projectId	string	true	Project ID
status	string	true	The processing state of project cleanup task.

Enumerated Values¶

Property	Value
status	[`ABORTED`, `BLOCKED`, `COMPLETED`, `CREATED`, `ERROR`, `EXPIRED`, `INCOMPLETE`, `INITIALIZED`, `PAUSED`, `RUNNING`]

ProjectRecover

{
  "action": "undelete"
}

Properties¶

Name	Type	Required	Restrictions	Description
action	string	true		Action to perform on a project

Enumerated Values¶

Property	Value
action	`undelete`

ProjectRecoverResponse

{
  "message": "string"
}

Properties¶

Name	Type	Required	Restrictions	Description
message	string	true		Operation result description

ProjectRetrieveResponse

{
  "advancedOptions": {
    "allowedPairwiseInteractionGroups": [
      [
        "string"
      ]
    ],
    "blendBestModels": true,
    "blueprintThreshold": 0,
    "considerBlendersInRecommendation": true,
    "defaultMonotonicDecreasingFeaturelistId": "string",
    "defaultMonotonicIncreasingFeaturelistId": "string",
    "downsampledMajorityRows": 0,
    "downsampledMinorityRows": 0,
    "eventsCount": "string",
    "exposure": "string",
    "majorityDownsamplingRate": 0,
    "minSecondaryValidationModelCount": true,
    "offset": [
      "string"
    ],
    "onlyIncludeMonotonicBlueprints": false,
    "prepareModelForDeployment": true,
    "responseCap": true,
    "runLeakageRemovedFeatureList": true,
    "scoringCodeOnly": true,
    "seed": "string",
    "shapOnlyMode": true,
    "smartDownsampled": true,
    "weights": "string"
  },
  "autopilotClusterList": [
    2
  ],
  "autopilotMode": "0",
  "catalogId": "string",
  "catalogVersionId": "string",
  "created": "2019-08-24T14:15:22Z",
  "externalTimeSeriesBaselineDatasetMetadata": {
    "datasetId": "string",
    "datasetName": "string"
  },
  "featureEngineeringPredictionPoint": "string",
  "fileName": "string",
  "holdoutUnlocked": true,
  "id": "string",
  "isScoringAvailableForModelsTrainedIntoValidationHoldout": true,
  "maxClusters": 2,
  "maxTrainPct": 0,
  "maxTrainRows": 0,
  "metric": "string",
  "minClusters": 2,
  "partition": {
    "cvHoldoutLevel": "string",
    "cvMethod": "random",
    "datetimeCol": "string",
    "datetimePartitionColumn": "string",
    "holdoutLevel": "string",
    "holdoutPct": 0,
    "partitionKeyCols": [
      "string"
    ],
    "reps": 0,
    "trainingLevel": "string",
    "useTimeSeries": true,
    "userPartitionCol": "string",
    "validationLevel": "string",
    "validationPct": 0,
    "validationType": "CV"
  },
  "positiveClass": "string",
  "primaryLocationColumn": "string",
  "projectName": "string",
  "queryGeneratorId": "string",
  "quickrun": true,
  "relationshipsConfigurationId": "string",
  "segmentation": {
    "parentProjectId": "string",
    "segment": "string",
    "segmentationTaskId": "string"
  },
  "stage": "modeling",
  "target": "string",
  "targetType": "Binary",
  "unsupervisedMode": true,
  "unsupervisedType": "anomaly",
  "useFeatureDiscovery": true,
  "useGpu": true
}

Properties¶

Name	Type	Required	Restrictions	Description
advancedOptions	ProjectAdvancedOptionsResponse	true		Information related to the current model of the deployment.
autopilotClusterList	[integer]¦null	false	maxItems: 10	Optional. A list of integers where each value will be used as the number of clusters in Autopilot model(s) for unsupervised clustering projects. Cannot be specified unless unsupervisedMode is true and unsupervisedType is set to 'clustering'.
autopilotMode	string¦null	true		The current autopilot mode. 0: Full Autopilot. 2: Manual Mode. 3: Quick Mode. 4: Comprehensive Autopilot. null: Mode not set.
catalogId	string¦null	true		The ID of the AI catalog entry used to create the project, or null if not created from the AI catalog.
catalogVersionId	string¦null	true		The ID of the AI catalog version used to create the project, or null if not created from the AI catalog.
created	string(date-time)	true		The time of project creation.
externalTimeSeriesBaselineDatasetMetadata	ExternalTSBaselineMetadata	false		The id of the catalog item that is being used as the external baseline data
featureEngineeringPredictionPoint	string¦null	false		The date column to be used as the prediction point for time-based feature engineering.
fileName	string	true		The name of the dataset used to create the project.
holdoutUnlocked	boolean	true		Whether the holdout has been unlocked.
id	string	true		The ID of the project.
isScoringAvailableForModelsTrainedIntoValidationHoldout	boolean	true		Indicates whether validation scores are available. A result of 'N/A' in the UI indicates that a model was trained into validation or holdout and also either does not have stacked predictions or uses extended multiclass.
maxClusters	integer¦null	false	maximum: 100 minimum: 2	Only valid when unsupervisedMode is True and unsupervisedType is 'clustering'. The maximum number of clusters allowed when training clustering models. If specified cannot be exceed the number of rows in a project's dataset divided by 50 and must be less than or equal to `minClusters`. If unsupervisedMode is True and unsupervisedType is 'clustering' then defaults to the number of rows in the project's dataset divided by 50 or 100 if that number of greater than 100.
maxTrainPct	number	true		The maximum percentage of the dataset that can be used to successfully train a model without going into the validation data.
maxTrainRows	integer	true		The maximum number of rows of the dataset that can be used to successfully train a model without going into the validation data.
metric	string	true		The metric used to select the best-performing models.
minClusters	integer¦null	false	maximum: 100 minimum: 2	Only valid when unsupervisedMode is True and unsupervisedType is 'clustering'. The minimum number of clusters allowed when training clustering models. If specified cannot be exceed the number of rows in a project's dataset divided by 50 and must be less than or equal to `maxClusters`. If unsupervisedMode is True and unsupervisedType is 'clustering' then defaults to 2.
partition	Partition	true		The partition object of a project indicates the settings used for partitioning. Depending on the partitioning selected, many of the options will be null.
positiveClass	any	true		If the project uses binary classification, the class designated to be the positive class.

oneOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false		none

xor

Name	Type	Required	Restrictions	Description
» anonymous	integer	false		none

continued

Name	Type	Required	Description
primaryLocationColumn	string	false	Primary location column name
projectName	string	true	The name of the project.
queryGeneratorId	string¦null	true	The ID of the time series data prep query generator associated with the project, or null if there is no associated query generator.
quickrun	boolean	true	If the Autopilot mode is set to quick. DEPRECATED: look at autopilot_mode instead.
relationshipsConfigurationId	string¦null	false	Relationships configuration id to be used for Feature Discovery projects.
segmentation	ProjectSegmentationInfoResponse	false	Segmentation info for the project.
stage	string	true	The stage of the project. If modeling, then the target is successfully set and modeling or predictions can proceed.
target	string	true	The target of the project, null if project is unsupervised.
targetType	string¦null	true	The type of the selected target. Null if the project is unsupervised.
unsupervisedMode	boolean¦null	true	Indicates whether a project is unsupervised.
unsupervisedType	string¦null	false	Only valid when unsupervisedMode is True. The type of unsupervised project, anomaly or clustering. If unsupervisedMode, defaults to 'anomaly'.
useFeatureDiscovery	boolean	true	Indicates whether a feature discovery project was created as opposed to a regular project
useGpu	boolean¦null	false	Indicates whether project should use GPU workers

Enumerated Values¶

Property	Value
autopilotMode	[`0`, `2`, `3`, `4`]
stage	[`modeling`, `aim`, `fasteda`, `eda`, `eda2`, `empty`]
targetType	[`Binary`, `Regression`, `Multiclass`, `Multilabel`]
unsupervisedType	[`anomaly`, `clustering`]

ProjectSegmentUpdate

{
  "operation": "restart"
}

Properties¶

Name	Type	Required	Restrictions	Description
operation	string	false		Name of operation to do on project segment

Enumerated Values¶

Property	Value
operation	`restart`

ProjectSegmentUpdateResponse

{
  "projectId": "string",
  "segmentId": "string"
}

Properties¶

Name	Type	Required	Restrictions	Description
projectId	string	true		New project id of the restarted segment
segmentId	string	true		The name of the restarted segment

ProjectSegmentationInfoResponse

{
  "parentProjectId": "string",
  "segment": "string",
  "segmentationTaskId": "string"
}

Segmentation info for the project.

Properties¶

Name	Type	Required	Description
parentProjectId	string¦null	false	ID of the original project.
segment	string¦null	false	Segment value.
segmentationTaskId	string	true	ID of the Segmentation Task.

ProjectStatusResponse

{
  "autopilotDone": true,
  "stage": "modeling",
  "stageDescription": "string"
}

Properties¶

Name	Type	Required	Description
autopilotDone	boolean	true	whether the current autopilot run has finished
stage	string	true	the current stage of the project, where modeling indicates that the target has been successfully set and modeling and predictions may proceed
stageDescription	string	true	a description of the current stage of the project

Enumerated Values¶

Property	Value
stage	[`modeling`, `aim`, `fasteda`, `eda`, `eda2`, `empty`]

ProjectUpdate

{
  "gpuWorkerCount": 0,
  "holdoutUnlocked": "True",
  "projectDescription": "string",
  "projectName": "string",
  "workerCount": 0
}

Properties¶

Name	Type	Required	Restrictions	Description
gpuWorkerCount	integer	false		The desired new number of gpu workers if the number of gpu workers should be changed. Must not exceed the number of gpu workers available to the user. `0` is allowed. `-1` requests the maximum number available to the user.
holdoutUnlocked	string	false		If specified, the holdout will be unlocked; note that the holdout cannot be relocked after unlocking
projectDescription	string	false	maxLength: 500	The new description of the project, if the description should be updated.
projectName	string	false	maxLength: 100	The new name of the project, if it should be renamed.
workerCount	integer	false		The desired new number of workers if the number of workers should be changed. Must not exceed the number of workers available to the user. `0` is allowed. (New in version v2.14) `-1` requests the maximum number available to the user.

Enumerated Values¶

Property	Value
holdoutUnlocked	`True`

S3Credentials

{
  "awsAccessKeyId": "string",
  "awsSecretAccessKey": "string",
  "awsSessionToken": null,
  "configId": "string",
  "credentialType": "s3"
}

Properties¶

Name	Type	Required	Description
awsAccessKeyId	string	false	The S3 AWS access key ID. Required if configId is not specified.Cannot include this parameter if configId is specified.
awsSecretAccessKey	string	false	The S3 AWS secret access key. Required if configId is not specified.Cannot include this parameter if configId is specified.
awsSessionToken	string¦null	false	The S3 AWS session token for AWS temporary credentials.Cannot include this parameter if configId is specified.
configId	string	false	ID of Secure configurations of credentials shared by admin.If specified, cannot include awsAccessKeyId, awsSecretAccessKey or awsSessionToken
credentialType	string	true	The type of these credentials, 's3' here.

Enumerated Values¶

Property	Value
credentialType	`s3`

SegmentationDataMappingResponse

{
  "segment": "string",
  "seriesId": "string"
}

Properties¶

Name	Type	Required	Restrictions	Description
segment	string	true		The segment name associated with the multiseries ID column by the segmentation task
seriesId	string	true		The multiseries ID column used to identify series for segmentation

SegmentationEDACompletedResponse

{
  "maxDate": "2019-08-24T14:15:22Z",
  "minDate": "2019-08-24T14:15:22Z",
  "name": "string",
  "numberOfRows": 0,
  "sizeInBytes": 0
}

Properties¶

Name	Type	Required	Restrictions	Description
maxDate	string(date-time)	true		Latest date in segment.
minDate	string(date-time)	true		Earliest date in segment.
name	string	true		Name of the segment.
numberOfRows	integer	true	minimum: 0 (exclusive)	Number of rows in segment.
sizeInBytes	integer	true	minimum: 0 (exclusive)	Size of segment in bytes.

SegmentationResultsCompletedResponse

{
  "name": "string",
  "segmentationTaskId": "string",
  "segmentsCount": 0,
  "segmentsEda": [
    {
      "maxDate": "2019-08-24T14:15:22Z",
      "minDate": "2019-08-24T14:15:22Z",
      "name": "string",
      "numberOfRows": 0,
      "sizeInBytes": 0
    }
  ],
  "url": "string"
}

Properties¶

Name	Type	Required	Description
name	string	true	Name of the segmentation task job
segmentationTaskId	string	true	Id of the completed segmentation task
segmentsCount	integer	true	Number of segments produced by the task
segmentsEda	[SegmentationEDACompletedResponse]	true	Array of segments EDA information.
url	string	true	Url to retrieve detailed information about the segmentation task

SegmentationResultsFailedResponse

{
  "message": "string",
  "name": "string",
  "parameters": {}
}

Properties¶

Name	Type	Required	Description
message	string	true	Response containing the error message from the segmentation task
name	string	true	Name of the segmentation task job
parameters	AllowExtra	true	Parameters submitted by the user to the failed job

SegmentationResultsResponse

{
  "completedJobs": [
    {
      "name": "string",
      "segmentationTaskId": "string",
      "segmentsCount": 0,
      "segmentsEda": [
        {
          "maxDate": "2019-08-24T14:15:22Z",
          "minDate": "2019-08-24T14:15:22Z",
          "name": "string",
          "numberOfRows": 0,
          "sizeInBytes": 0
        }
      ],
      "url": "string"
    }
  ],
  "failedJobs": [
    {
      "message": "string",
      "name": "string",
      "parameters": {}
    }
  ],
  "numberOfJobs": 0
}

Properties¶

Name	Type	Required	Description
completedJobs	[SegmentationResultsCompletedResponse]	true	List of completed segmentation tasks
failedJobs	[SegmentationResultsFailedResponse]	true	List of failed segmentation tasks
numberOfJobs	integer	true	Total number of completed and failed jobs processed

SegmentationTaskCreate

{
  "datetimePartitionColumn": "string",
  "modelPackageId": "string",
  "multiseriesIdColumns": [
    "string"
  ],
  "target": "string",
  "useAutomatedSegmentation": false,
  "useTimeSeries": false,
  "userDefinedSegmentIdColumns": [
    "string"
  ]
}

Properties¶

Name	Type	Required	Restrictions	Description
datetimePartitionColumn	string	false		The date column that will be used to identify the date in time series segmentation.
modelPackageId	string	false		Model package id for using an external model registry package.
multiseriesIdColumns	[string]	false	maxItems: 1 minItems: 1	List of one or more names of multiseries id columns.
target	string	true		The target for the dataset
useAutomatedSegmentation	boolean	false		Enable the use of automated segmentation tasks
useTimeSeries	boolean	false		Enable time series based segmentation tasks
userDefinedSegmentIdColumns	[string]	false	minItems: 1	List of one or more names of columns to be used for user-defined business rule segmentations.

SegmentationTaskDataResponse

{
  "clusteringModelId": "string",
  "clusteringModelName": "string",
  "clusteringProjectId": "string",
  "datetimePartitionColumn": "string",
  "modelPackageId": "string",
  "multiseriesIdColumns": [
    "string"
  ],
  "userDefinedSegmentIdColumns": [
    "string"
  ]
}

Data for the segmentation task

Properties¶

Name	Type	Required	Description
clusteringModelId	string¦null	false	Id of the model used by the segmentation task for automated segmentation
clusteringModelName	string¦null	false	Name of the model used by the segmentation task for automated segmentation
clusteringProjectId	string¦null	false	Id of the project used by the segmentation task for automated segmentation
datetimePartitionColumn	string	false	Name of the datetime partitioning column used by the segmentation task
modelPackageId	string	false	External model package id used by the segmentation task for automated segmentation
multiseriesIdColumns	[string]	false	The multiseries id columns used by the segmentation task
userDefinedSegmentIdColumns	[string]	false	The user defined segmentation columns used by the segmentation task

SegmentationTaskListResponse

{
  "count": 0,
  "data": [
    {
      "created": "2019-08-24T14:15:22Z",
      "data": {
        "clusteringModelId": "string",
        "clusteringModelName": "string",
        "clusteringProjectId": "string",
        "datetimePartitionColumn": "string",
        "modelPackageId": "string",
        "multiseriesIdColumns": [
          "string"
        ],
        "userDefinedSegmentIdColumns": [
          "string"
        ]
      },
      "metadata": {
        "useAutomatedSegmentation": true,
        "useMultiseriesIdColumns": true,
        "useTimeSeries": true
      },
      "name": "string",
      "projectId": "string",
      "segmentationTaskId": "string",
      "segments": [
        "string"
      ],
      "segmentsCount": 0,
      "segmentsEda": [
        {
          "maxDate": "2019-08-24T14:15:22Z",
          "minDate": "2019-08-24T14:15:22Z",
          "name": "string",
          "numberOfRows": 0,
          "sizeInBytes": 0
        }
      ],
      "type": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Properties¶

Name	Type	Required	Description
count	integer	false	Number of items returned on this page.
data	[SegmentationTaskResponse]	true	List of the segmentation tasks that are associated with the project Id.
next	string(uri)¦null	true	URL pointing to the next page (if null, there is no next page).
previous	string(uri)¦null	true	URL pointing to the previous page (if null, there is no previous page).

SegmentationTaskMetadataResponse

{
  "useAutomatedSegmentation": true,
  "useMultiseriesIdColumns": true,
  "useTimeSeries": true
}

Metadata for the segmentation task

Properties¶

Name	Type	Required	Description
useAutomatedSegmentation	boolean	true	Segmentation task uses automated segmentation
useMultiseriesIdColumns	boolean	true	Segmentation task uses a multiseries column
useTimeSeries	boolean	true	Segmentation task is a time series task

SegmentationTaskResponse

{
  "created": "2019-08-24T14:15:22Z",
  "data": {
    "clusteringModelId": "string",
    "clusteringModelName": "string",
    "clusteringProjectId": "string",
    "datetimePartitionColumn": "string",
    "modelPackageId": "string",
    "multiseriesIdColumns": [
      "string"
    ],
    "userDefinedSegmentIdColumns": [
      "string"
    ]
  },
  "metadata": {
    "useAutomatedSegmentation": true,
    "useMultiseriesIdColumns": true,
    "useTimeSeries": true
  },
  "name": "string",
  "projectId": "string",
  "segmentationTaskId": "string",
  "segments": [
    "string"
  ],
  "segmentsCount": 0,
  "segmentsEda": [
    {
      "maxDate": "2019-08-24T14:15:22Z",
      "minDate": "2019-08-24T14:15:22Z",
      "name": "string",
      "numberOfRows": 0,
      "sizeInBytes": 0
    }
  ],
  "type": "string"
}

Properties¶

Name	Type	Required	Description
created	string(date-time)	true	Date and time when the segmentation task was originally created
data	SegmentationTaskDataResponse	true	Data for the segmentation task
metadata	SegmentationTaskMetadataResponse	true	Metadata for the segmentation task
name	string	true	Name of the segmentation task
projectId	string	true	Id of the parent project associated with the segmentation task
segmentationTaskId	string	true	Id of the segmentation task
segments	[string]	true	Names of the unique segments generated by the segmentation task
segmentsCount	integer	true	Number of segments generated by the segmentation task
segmentsEda	[SegmentationEDACompletedResponse]	true	Array of segments EDA information.
type	string	true	Type of segmentation task (e.g. AutoML, AutoTS)

SegmentationTaskSegmentMappingsResponse

{
  "count": 0,
  "data": [
    {
      "segment": "string",
      "seriesId": "string"
    }
  ],
  "next": "http://example.com",
  "previous": "http://example.com"
}

Properties¶

Name	Type	Required	Description
count	integer	false	Number of items returned on this page.
data	[SegmentationDataMappingResponse]	true	An array of segmentation mappings.
next	string(uri)¦null	true	URL pointing to the next page (if null, there is no next page).
previous	string(uri)¦null	true	URL pointing to the previous page (if null, there is no previous page).

SharingListResponse

{
  "count": 0,
  "data": [
    {
      "canShare": true,
      "role": "string",
      "userId": "string",
      "username": "string"
    }
  ],
  "next": "string",
  "previous": "string"
}

Properties¶

Name	Type	Required	Description
count	integer	true	The number of items returned.
data	[AccessControl]	true	The access control list.
next	string¦null	true	URL pointing to the next page.
previous	string¦null	true	URL pointing to the previous page.

SharingUpdateOrRemove

{
  "data": [
    {
      "role": "ADMIN",
      "username": "string"
    }
  ],
  "includeFeatureDiscoveryEntities": false,
  "sendNotification": true
}

Properties¶

Name	Type	Required	Restrictions	Description
data	[UpdateAccessControl]	true	maxItems: 100	The role to set for the user.
includeFeatureDiscoveryEntities	boolean	false		Whether to share all the related entities.
sendNotification	boolean	false		Send an email notification.

SnowflakeKeyPairCredentials

{
  "configId": "string",
  "credentialType": "snowflake_key_pair_user_account",
  "passphrase": "string",
  "privateKeyStr": "string",
  "user": "string"
}

Properties¶

Name	Type	Required	Description
configId	string	false	The ID of the saved shared credentials. If specified, cannot include user, privateKeyStr or passphrase.
credentialType	string	true	The type of these credentials, 'snowflake_key_pair_user_account' here.
passphrase	string	false	Optional passphrase to decrypt private key. Cannot include this parameter if configId is specified.
privateKeyStr	string	false	Private key for key pair authentication. Required if configId is not specified. Cannot include this parameter if configId is specified.
user	string	false	Username for this credential. Required if configId is not specified. Cannot include this parameter if configId is specified.

Enumerated Values¶

Property	Value
credentialType	`snowflake_key_pair_user_account`

UpdateAccessControl

{
  "role": "ADMIN",
  "username": "string"
}

Properties¶

Name	Type	Required	Restrictions	Description
role	string¦null	true		The role to set for the user.
username	string	true		The username of the user to set the role for.

Enumerated Values¶

Property	Value
role	[`ADMIN`, `CONSUMER`, `DATA_SCIENTIST`, `EDITOR`, `OBSERVER`, `OWNER`, `READ_ONLY`, `READ_WRITE`, `USER`]