The Describe tabs provide model building information and feature details:
|Blueprint||Provides a graphical representation of the data preprocessing and parameter settings via blueprint.||Blueprint structure is decided once (by the metablueprint after the partitioning stage), taking project options, dataset shape, and column metadata into account. Values of some hyperparameters (‘auto’) may be decided later during training. Certain blueprint inputs and paths can be eliminated before training if the feature list does not have the corresponding feature types.|
|Coefficients||Provides, for select models, a visual representation of the most important variables and a coefficient export capability.||Training data|
|Constraints||Forces certain XGBoost models to learn only monotonic (always increasing or always decreasing) relationships between specific features and the target.||Training, Validation data|
|Data Quality Handling Report (Formerly Missing Values)||Provides transformation and imputation information for uncensored blueprints.||Training data|
|Eureqa Models||Provides access to model blueprints for Eureqa generalized additive models (GAM), regression models, and classification models.||The Pareto front uses the Eureqa validation set, a subset of DataRobot training. The plots shown for regression and classification models use validation data.|
|Log||Lists operation status results.||N/A|
|Model Info||Displays model information.||Training data|
|Rating Table||Provides access to an export of the model’s complete, validated parameters.||Training data|
Updated September 2, 2021
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