build/lib/AutoMxL/__main__.py
def select_features_apply(self, df, verbose=False):
        """Apply features selection.

         Requires Select_Features method to have been applied

         Parameters
         ----------
         df : DataFrame
             dataset to apply selection on
         verbose : boolean (Default False)
             Get logging information

         Returns
         -------
         DataFrame : reduced dataset
         """
        # check pipe step and is_fitted
        assert self.is_fitted_selector, "fit first (please)"

        if verbose:
            start_time = time()
            print_title1('Apply select_features')

        df_local = df.copy()

        df_local = self.features_selector.transform(df_local, verbose=verbose)

        if verbose:
            print('\n\t\t>>>', 'select_features_apply execution time:', round(time() - start_time, 4), 'secs. <<<')

        return df_local
Apply features selection.

         Requires Select_Features method to have been applied

         Parameters
         ----------
         df : DataFrame
             dataset to apply selection on
         verbose : boolean (Default False)
             Get logging information

         Returns
         -------
         DataFrame : reduced dataset
         
Apply features selection.
Requires Select_Features method to have been applied

Parameters

df : DataFrame
dataset to apply selection on
verbose : boolean (Default False)
Get logging information

Returns

DataFrame : reduced dataset
Apply features selection . Requires Select_Features method to have been applied Parameters df : DataFrame dataset to apply selection on verbose : boolean ( Default False ) Get logging information Returns DataFrame : reduced dataset
def select_features_apply(self, df, verbose=False):
        assert self.is_fitted_selector, "fit first (please)"
        if verbose:
            start_time = time()
            print_title1('Apply select_features')
        df_local = df.copy()
        df_local = self.features_selector.transform(df_local, verbose=verbose)
        if verbose:
            print('\n\t\t>>>', 'select_features_apply execution time:', round(time() - start_time, 4), 'secs. <<<')
        return df_local
def select_features_apply ( self , df , verbose = False ) : assert self . is_fitted_selector , "fit first (please)" if verbose : start_time = time ( ) print_title1 ( 'Apply select_features' ) df_local = df . copy ( ) df_local = self . features_selector . transform ( df_local , verbose = verbose ) if verbose : print ( '\n\t\t>>>' , 'select_features_apply execution time:' , round ( time ( ) - start_time , 4 ) , 'secs. <<<' ) return df_local
Apply features selection.
Apply features selection .
"""Apply features selection.

         Requires Select_Features method to have been applied

         Parameters
         ----------
         df : DataFrame
             dataset to apply selection on
         verbose : boolean (Default False)
             Get logging information

         Returns
         -------
         DataFrame : reduced dataset
         """ # check pipe step and is_fitted
self
df
verbose