get_model_relevance_table

get_model_relevance_table(df: pandas.core.frame.DataFrame, df_exog: pandas.core.frame.DataFrame, model: Union[sklearn.tree._classes.DecisionTreeRegressor, sklearn.tree._classes.ExtraTreeRegressor, sklearn.ensemble._forest.RandomForestRegressor, sklearn.ensemble._forest.ExtraTreesRegressor, sklearn.ensemble._gb.GradientBoostingRegressor, catboost.core.CatBoostRegressor]) → pandas.core.frame.DataFrame

Calculate relevance table with feature importance from model.

Parameters

• df (pandas.core.frame.DataFrame) – dataframe with timeseries

• df_exog (pandas.core.frame.DataFrame) – dataframe with exogenous data

• model (Union[sklearn.tree._classes.DecisionTreeRegressor, sklearn.tree._classes.ExtraTreeRegressor, sklearn.ensemble._forest.RandomForestRegressor, sklearn.ensemble._forest.ExtraTreesRegressor, sklearn.ensemble._gb.GradientBoostingRegressor, catboost.core.CatBoostRegressor]) – model to obtain feature importance, should have feature_importances_ property

Returns

dataframe with feature importance values.

Return type

pd.DataFrame