| 1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253 |
- #
- # Copyright 2019 The FATE Authors. All Rights Reserved.
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- #
- import numpy as np
- from federatedml.util import LOGGER
- from federatedml.util import consts
- class BaseCrossValidator(object):
- def __init__(self):
- self.mode = None
- self.role = None
- def split(self, data_inst):
- pass
- def display_cv_result(self, cv_results):
- LOGGER.debug("cv_result: {}".format(cv_results))
- if self.role == consts.GUEST or (self.role == consts.HOST and self.mode == consts.HOMO):
- format_cv_result = {}
- for eval_result in cv_results:
- for eval_name, eval_r in eval_result.items():
- if not isinstance(eval_r, list):
- if eval_name not in format_cv_result:
- format_cv_result[eval_name] = []
- format_cv_result[eval_name].append(eval_r)
- else:
- for e_r in eval_r:
- e_name = "{}_thres_{}".format(eval_name, e_r[0])
- if e_name not in format_cv_result:
- format_cv_result[e_name] = []
- format_cv_result[e_name].append(e_r[1])
- for eval_name, eva_result_list in format_cv_result.items():
- mean_value = np.around(np.mean(eva_result_list), 4)
- std_value = np.around(np.std(eva_result_list), 4)
- LOGGER.info("{}，evaluate name: {}, mean: {}, std: {}".format(self.role,
- eval_name, mean_value, std_value))
|
