<model_name>!EXPLAIN_FEATURE_IMPORTANCE

Returns the relative feature importance for each feature used by the model.

Syntax

<model_name>!EXPLAIN_FEATURE_IMPORTANCE();
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Output

The SERIES column is present only for multi-series forecasts. Single-series forecasts do not have this column.

Column

Type

Description

SERIES

VARIANT

Series value (if model was trained with multiple time series).

RANK

INTEGER

The importance rank of a feature for a particular series.

FEATURE_NAME

VARCHAR

The name of the feature used to train the model. aggregated_endogenous_features represents all features derived as transformations of the target variable.

IMPORTANCE_SCORE

FLOAT

The feature’s importance score: a value in [0, 1], with 0 being the lowest possible importance, and 1 the highest.

FEATURE_TYPE

VARCHAR

The source of the feature. One of:

  • user_provided: Feature data provided by the user.

  • derived_from_timestamp: Periodic feature (e.g. day, week, or month) derived from timestamp data.

  • derived_from_endogenous: Features derived from a transformation of the target variable.

Examples

See Examples.