def export(self, output_file_name):
        """exports engineered features

        Parameters
        ----------
        output_file_name: string
            String containing the path and file name of the desired output file

        Returns
        -------
        None

        """
        if self._best_estimator is None:
            raise ValueError('A model has not been optimized. Please call fit()'
                             ' first.')

        # Write print_model() to file
        with open(output_file_name, 'w') as output_file:
            output_file.write(self.print_model())
        # if decision tree, print tree into dot file
        if 'DecisionTree' in self.ml_type:
            export_graphviz(self._best_estimator,
                            out_file=output_file_name+'.dot',
                            feature_names = self.stacks_2_eqns(self._best_inds)
                            if self._best_inds else None,
                            class_names=['True','False'],
                            filled=False,impurity = True,rotate=True)
def export ( self , output_file_name ) : if self . _best_estimator is None : raise ValueError ( 'A model has not been optimized. Please call fit()' ' first.' ) with open ( output_file_name , 'w' ) as output_file : output_file . write ( self . print_model ( ) ) if 'DecisionTree' in self . ml_type : export_graphviz ( self . _best_estimator , out_file = output_file_name + '.dot' , feature_names = self . stacks_2_eqns ( self . _best_inds ) if self . _best_inds else None , class_names = [ 'True' , 'False' ] , filled = False , impurity = True , rotate = True )
exports engineered features

        Parameters
        ----------
        output_file_name: string
            String containing the path and file name of the desired output file

        Returns
        -------
        None