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- #!/usr/bin/env python
- # -*- coding: utf-8 -*-
- #
- # 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.
- from pipeline.param.base_param import BaseParam
- from pipeline.param import consts
- class StepwiseParam(BaseParam):
- """
- Define stepwise params
- Parameters
- ----------
- score_name: {"AIC", "BIC"}, default: 'AIC'
- Specify which model selection criterion to be used
- mode: {"Hetero", "Homo"}, default: 'Hetero'
- Indicate what mode is current task
- role: {"Guest", "Host", "Arbiter"}, default: 'Guest'
- Indicate what role is current party
- direction: {"both", "forward", "backward"}, default: 'both'
- Indicate which direction to go for stepwise.
- 'forward' means forward selection; 'backward' means elimination; 'both' means possible models of both directions are examined at each step.
- max_step: int, default: '10'
- Specify total number of steps to run before forced stop.
- nvmin: int, default: '2'
- Specify the min subset size of final model, cannot be lower than 2. When nvmin > 2, the final model size may be smaller than nvmin due to max_step limit.
- nvmax: int, default: None
- Specify the max subset size of final model, 2 <= nvmin <= nvmax. The final model size may be larger than nvmax due to max_step limit.
- need_stepwise: bool, default False
- Indicate if this module needed to be run
- """
- def __init__(self, score_name="AIC", mode=consts.HETERO, role=consts.GUEST, direction="both",
- max_step=10, nvmin=2, nvmax=None, need_stepwise=False):
- super(StepwiseParam, self).__init__()
- self.score_name = score_name
- self.mode = mode
- self.role = role
- self.direction = direction
- self.max_step = max_step
- self.nvmin = nvmin
- self.nvmax = nvmax
- self.need_stepwise = need_stepwise
- def check(self):
- model_param_descr = "stepwise param's"
- self.score_name = self.check_and_change_lower(self.score_name, ["aic", "bic"], model_param_descr)
- self.check_valid_value(self.mode, model_param_descr, valid_values=[consts.HOMO, consts.HETERO])
- self.check_valid_value(self.role, model_param_descr, valid_values=[consts.HOST, consts.GUEST, consts.ARBITER])
- self.direction = self.check_and_change_lower(self.direction, ["forward", "backward", "both"], model_param_descr)
- self.check_positive_integer(self.max_step, model_param_descr)
- self.check_positive_integer(self.nvmin, model_param_descr)
- if self.nvmin < 2:
- raise ValueError(model_param_descr + " nvmin must be no less than 2.")
- if self.nvmax is not None:
- self.check_positive_integer(self.nvmax, model_param_descr)
- if self.nvmin > self.nvmax:
- raise ValueError(model_param_descr + " nvmax must be greater than nvmin.")
- self.check_boolean(self.need_stepwise, model_param_descr)
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