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- #
- # 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 unittest
- import numpy as np
- from federatedml.ensemble import XgboostCriterion
- from federatedml.util import consts
- class TestXgboostCriterion(unittest.TestCase):
- def setUp(self):
- self.reg_lambda = 0.3
- self.criterion = XgboostCriterion(reg_lambda=self.reg_lambda)
- def test_init(self):
- self.assertTrue(np.fabs(self.criterion.reg_lambda - self.reg_lambda) < consts.FLOAT_ZERO)
- def test_split_gain(self):
- node = [0.5, 0.6]
- left = [0.1, 0.2]
- right = [0.4, 0.4]
- gain_all = node[0] * node[0] / (node[1] + self.reg_lambda)
- gain_left = left[0] * left[0] / (left[1] + self.reg_lambda)
- gain_right = right[0] * right[0] / (right[1] + self.reg_lambda)
- split_gain = gain_left + gain_right - gain_all
- self.assertTrue(np.fabs(self.criterion.split_gain(node, left, right) - split_gain) < consts.FLOAT_ZERO)
- def test_node_gain(self):
- grad = 0.5
- hess = 6
- gain = grad * grad / (hess + self.reg_lambda)
- self.assertTrue(np.fabs(self.criterion.node_gain(grad, hess) - gain) < consts.FLOAT_ZERO)
- def test_node_weight(self):
- grad = 0.5
- hess = 6
- weight = -grad / (hess + self.reg_lambda)
- self.assertTrue(np.fabs(self.criterion.node_weight(grad, hess) - weight) < consts.FLOAT_ZERO)
- if __name__ == '__main__':
- unittest.main()
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