h2o-py/h2o/grid/grid_search.py
def show(self):
        """Print models sorted by metric."""
        hyper_combos = itertools.product(*list(self.hyper_params.values()))
        if not self.models:
            c_values = [[idx + 1, list(val)] for idx, val in enumerate(hyper_combos)]
            print(H2OTwoDimTable(
                col_header=['Model', 'Hyperparameters: [' + ', '.join(list(self.hyper_params.keys())) + ']'],
                table_header='Grid Search of Model ' + self.model.__class__.__name__, cell_values=c_values))
        else:
            print(self.sorted_metric_table())
def show(self):
        hyper_combos = itertools.product(*list(self.hyper_params.values()))
        if not self.models:
            c_values = [[idx + 1, list(val)] for idx, val in enumerate(hyper_combos)]
            print(H2OTwoDimTable(
                col_header=['Model', 'Hyperparameters: [' + ', '.join(list(self.hyper_params.keys())) + ']'],
                table_header='Grid Search of Model ' + self.model.__class__.__name__, cell_values=c_values))
        else:
            print(self.sorted_metric_table())
def show ( self ) : hyper_combos = itertools . product ( * list ( self . hyper_params . values ( ) ) ) if not self . models : c_values = [ [ idx + 1 , list ( val ) ] for idx , val in enumerate ( hyper_combos ) ] print ( H2OTwoDimTable ( col_header = [ 'Model' , 'Hyperparameters: [' + ', ' . join ( list ( self . hyper_params . keys ( ) ) ) + ']' ] , table_header = 'Grid Search of Model ' + self . model . __class__ . __name__ , cell_values = c_values ) ) else : print ( self . sorted_metric_table ( ) )
Print models sorted by metric.
Print models sorted by metric .