<model_name>!EXPLAIN_FEATURE_IMPORTANCE¶

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

If you need to select specific columns from the data returned by this method, you can call the method in the FROM clause of a SELECT statement. See Selecting columns from SQL class instance methods that return tabular data.

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).
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.