<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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Column	Type	Description
SERIES	VARIANT	Series value (NULL if model was trained with single time series). Note Your single-series results may not have a SERIES column. See recent change.
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.