2ab8c1444facbd46df8767a5badda5b9f1a50c29,tpot/tpot.py,TPOT,predict,#TPOT#Any#,314

Before Change

        new_col_names = {}
        for column in training_testing_data.columns.values:
            if type(column) != str:
                new_col_names[column] = str(column).zfill(10)
        training_testing_data.rename(columns=new_col_names, inplace=True)

        // Transform the tree expression in a callable function
        func = self._toolbox.compile(expr=self._optimized_pipeline)

After Change

        most_frequent_class = Counter(self._training_classes).most_common(1)[0][0]
        data = np.concatenate([training_data, testing_data])
        data = np.insert(data, 0, np.array([most_frequent_class] * data.shape[0]), axis=1)

        // Transform the tree expression in a callable function
        func = self._toolbox.compile(expr=self._optimized_pipeline)

Instances