示例#1
0
    def _get_meta(self):
        # col_list = [str(x) for x in self.cols]

        transform_param = feature_binning_meta_pb2.TransformMeta(
            transform_cols=self.bin_inner_param.transform_bin_indexes,
            transform_type=self.model_param.transform_param.transform_type)

        meta_protobuf_obj = feature_binning_meta_pb2.FeatureBinningMeta(
            method=self.model_param.method,
            compress_thres=self.model_param.compress_thres,
            head_size=self.model_param.head_size,
            error=self.model_param.error,
            bin_num=self.model_param.bin_num,
            cols=self.bin_inner_param.bin_names,
            adjustment_factor=self.model_param.adjustment_factor,
            local_only=self.model_param.local_only,
            need_run=self.need_run,
            transform_param=transform_param)
        return meta_protobuf_obj
示例#2
0
    def _get_meta(self):
        col_list = [str(x) for x in self.cols]
        LOGGER.debug("In get_meta, transform_cols_idx: {}".format(
            self.transform_cols_idx))
        if not isinstance(self.transform_cols_idx, (list, tuple)):
            self.transform_cols_idx = []
        transform_param = feature_binning_meta_pb2.TransformMeta(
            transform_cols=self.transform_cols_idx,
            transform_type=self.model_param.transform_param.transform_type)

        meta_protobuf_obj = feature_binning_meta_pb2.FeatureBinningMeta(
            method=self.model_param.method,
            compress_thres=self.model_param.compress_thres,
            head_size=self.model_param.head_size,
            error=self.model_param.error,
            bin_num=self.model_param.bin_num,
            cols=col_list,
            adjustment_factor=self.model_param.adjustment_factor,
            local_only=self.model_param.local_only,
            need_run=self.need_run,
            transform_param=transform_param)
        return meta_protobuf_obj