def __add_target_data(self, transformed_data, original_data): """ Picks up the target data from the original_data and appends it as a column to the transformed_data. Both arguments are expected to be np.array's. """ model = self.__config.get_data_model() target_feature = model.find_target_feature() name = target_feature.get_name() if target_feature.is_categorical(): target_row = original_data[name] target = self.__label_encoder_adapter.transform(target_row) else: target = original_data[name].values.astype(type_name_to_data_type("float")) target = target[..., None] return np.hstack((transformed_data, target))
def __add_target_data(self, transformed_data, original_data): """ Picks up the target data from the original_data and appends it as a column to the transformed_data. Both arguments are expected to be np.array's. """ model = self.__config.get_data_model() target_feature = model.find_target_feature() name = target_feature.get_name() if target_feature.is_categorical(): target_row = original_data[name] target = self.__label_encoder_adapter.transform(target_row) else: target = original_data[name].values.astype( type_name_to_data_type("float")) target = target[..., None] return np.hstack((transformed_data, target))
def is_type_name(self, type_name): return type_name_to_data_type(self.get_type_name()) == type_name_to_data_type(type_name)