Source code for autogluon.features.generators.label_encoder

import copy
import logging

from pandas import DataFrame

from autogluon.common.features.types import R_CATEGORY, S_TEXT_AS_CATEGORY

from .abstract import AbstractFeatureGenerator

logger = logging.getLogger(__name__)


# TODO: LabelEncoderTransformer
[docs] class LabelEncoderFeatureGenerator(AbstractFeatureGenerator): """Converts category features to int features by mapping to the category codes.""" def _fit_transform(self, X: DataFrame, **kwargs) -> (DataFrame, dict): X_out = self._transform(X) feature_metadata_out_type_group_map_special = copy.deepcopy(self.feature_metadata_in.type_group_map_special) if S_TEXT_AS_CATEGORY in feature_metadata_out_type_group_map_special: feature_metadata_out_type_group_map_special.pop(S_TEXT_AS_CATEGORY) return X_out, feature_metadata_out_type_group_map_special def _transform(self, X: DataFrame) -> DataFrame: return self.convert_category_to_int(X) @staticmethod def get_default_infer_features_in_args() -> dict: return dict(valid_raw_types=[R_CATEGORY]) @staticmethod def convert_category_to_int(X: DataFrame) -> DataFrame: # TODO: add inplace option? X = X.apply(lambda x: x.cat.codes) return X def _more_tags(self): return {"feature_interactions": False}