etna.analysis.get_model_relevance_table#
- get_model_relevance_table(df: DataFrame, df_exog: DataFrame, model: DecisionTreeRegressor | ExtraTreeRegressor | RandomForestRegressor | ExtraTreesRegressor | GradientBoostingRegressor | CatBoostRegressor) DataFrame[source]#
Calculate relevance table with feature importance from model.
- Parameters:
df (DataFrame) – dataframe with timeseries
df_exog (DataFrame) – dataframe with exogenous data
model (DecisionTreeRegressor | ExtraTreeRegressor | RandomForestRegressor | ExtraTreesRegressor | GradientBoostingRegressor | CatBoostRegressor) – model to obtain feature importance, should have
feature_importances_property
- Returns:
dataframe with feature importance values.
- Return type: