Register DataRobot models¶
After you create an experiment and train models, you can register one or more models from Workbench or directly in the Registry. If a registered model already exists to solve a specific business problem, you can add new models solving the same problem as registered model versions, providing a model management experience organized by problem type.
Register a model from Workbench¶
To register a model from a Workbench experiment:
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In a Workbench experiment, select the model from the Models list and then click Model actions > Register model:
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In the Register a model panel, under Configure the model, select one of the following:
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Add a version to an existing registered model: Increment the version number and add a new version to the selected registered model.
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Create a new registered model: Create a registered model and the first version (V1).
Then, configure the following fields:
Field Description Registered model name / Registered model Do one of the following: - Registered model name: When registering a new model, enter a unique and descriptive name for the new registered model. If you choose a name that exists anywhere within your organization, a warning appears.
- Registered model: When saving as a version of an existing model, select the existing registered model you want to add a new version to.
Registered version name Automatically populated with the model name, date, and time. Change or modify the name as necessary. Registered model version Assigned automatically. This displays the expected version number of the version (e.g., V1, V2, V3) you create. This is always V1 when you select Register as a new model. Prediction threshold For binary classification models. Enter the value a prediction score must exceed to be assigned to the positive class. The default value is 0.5
.If necessary, you can configure the following Optional settings:
Field Description Registered version description Enter a description of the business problem this model package solves, or, more generally, describe the model represented by this version. Tags Click + Add tag and enter a Key and a Value for each key-value pair you want to tag the model version with. Tags added when registering a new model are applied to V1. Include prediction intervals For time series models. Enable the computation of a model's time series prediction intervals (from 1 to 100). Time series prediction intervals may take a long time to compute, depending on the number of series in the dataset, the number of features, the blueprint, etc. Consider if intervals are required in your deployment before enabling this setting. Prediction intervals in DataRobot serverless prediction environments
In a DataRobot serverless prediction environment, to make predictions with time-series prediction intervals included, you must include pre-computed prediction intervals when registering the model package. If you don't pre-compute prediction intervals, the deployment resulting from the registered model doesn't support enabling prediction intervals.
Returning to Workbench
If you click Close on this page to return to Workbench, you lose the configuration progress on this page.
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Click Register model.
The model version opens on the Registry > Directory page with a Building status. You can deploy the model at any time.
Register a model from the Registry¶
To register a model from the Registry:
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In the Registry, on the Model directory tab, click + Register model (or the button when the registered model or version info panel is open):
The Register a model panel opens to the External model tab.
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Click the DataRobot model tab and then, under Configure the model, select one of the following options:
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Add a version to an existing registered model: Increment the version number and add a new version to the selected registered model.
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Create a new registered model: Create a registered model and the first version (V1).
Then, configure the following fields:
Field Description Use Case Select the Use Case in Workbench containing the model you want to register. Experiment Select the experiment in Workbench containing the model you want to register. DataRobot Model Select the model you want to register. Registered model name / Registered model Do one of the following: - Registered model name: When registering a new model, enter a unique and descriptive name for the new registered model. If you choose a name that exists anywhere within your organization, a warning appears.
- Registered model: When saving as a version of an existing model, select the existing registered model you want to add a new version to.
Registered version name Automatically populated with the model name, date, and time. Change or modify the name as necessary. Registered model version Assigned automatically. This displays the expected version number of the version (e.g., V1, V2, V3) you create. This is always V1 when you select Register as a new model. Prediction threshold For binary classification models. Enter the value a prediction score must exceed to be assigned to the positive class. The default value is 0.5
.Optional settings Registered version description Enter a description of the business problem this model package solves, or, more generally, describe the model represented by this version. Tags Click + Add tag and enter a Key and a Value for each key-value pair you want to tag the model version with. Tags added when registering a new model are applied to V1. Include prediction intervals For time series models. Enable the computation of a model's time series prediction intervals (from 1 to 100). Time series prediction intervals may take a long time to compute, depending on the number of series in the dataset, the number of features, the blueprint, etc. Consider if intervals are required in your deployment before enabling this setting. Prediction intervals in DataRobot serverless prediction environments
In a DataRobot serverless prediction environment, to make predictions with time-series prediction intervals included, you must include pre-computed prediction intervals when registering the model package. If you don't pre-compute prediction intervals, the deployment resulting from the registered model doesn't support enabling prediction intervals.
Returning to Workbench
If you click Cancel on this page to return to the Registry, you lose the configuration progress on this page.
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Click Register Model.
The model version opens on the Registry > Directory page with a Building status. You can deploy the model at any time.