The sections described below provide information to help you easily navigate the ML modeling process.
|Elements of the basic modeling workflow.
|Setting advanced modeling parameters prior to building.
|Manage models and projects, and export data.
Model insights (Leaderboard tabs)¶
|View key plots and statistics needed to judge and interpret a model’s effectiveness.
|Understand what drives a model’s predictions.
|View model building information and feature details.
|Make predictions in DataRobot using the UI or API.
|Compile model development documentation that can be used for regulatory validation.
|Add comments to assets in the AI Catalog.
|Bias and Fairness tabs
|Identify if a model is biased and why the model is learning bias from the training data.
|Other model tabs
|Compare models across a project.
|Build models with time-relevant data (not time series).
|Work with unlabeled or partially labeled data to build anomaly detection or clustering models.
|Build blueprints using built-in DataRobot tasks and custom Python or R code.
|Use image-based datasets.
|Use geospatial datasets.
Time series modeling¶
|What is time-based modeling?
|The basic modeling process and a recommended reading path.
|Time series workflow overview
|The workflow for creating a time series project.
|Time series insights
|Visualizations available to help interpret your data and models.
|Time series predictions
|Making predictions with time series models.
|Modeling with datasets that contain multiple time series.
|Grouping series into segments, creating multiple projects for each segment, and producing a single Combined Model for the data.
|Making predictions for the present and very near future (very short-range forecasting).
|Enable external prediction comparison
|Comparing model predictions built outside of DataRobot against DataRobot predictions.
|Advanced time series modeling
|Modifying partitions, setting advanced options, and understanding window settings.
|Time series modeling data
|Working with the time series modeling dataset:
|Time series reference
|How to customize time series projects as well as a variety of deep-dive reference material for DataRobot time series modeling.
|Data and sharing
|Dataset requirements, sharing assets, and permissions.
|The Leaderboard and the processes that drive model building, including partitioning and feature derivation.
|Eureqa advanced tuning
|Tune Eureqa models by modifying building blocks, customizing the target expression, and modifying other model parameters.
|A list of frequently asked modeling questions, including building models and model insights, with brief answers and links to more complete documentation.