Classifier.py 文件源码

def setBestParameters(self):
        cv = StratifiedKFold(n_splits = self.conf.num_folds)
        param_grid = self.conf.getParamGrid()
        if param_grid is None:
            # No parameter value to select
            return
        if self.conf.families_supervision:
            scoring = 'f1_macro'
        else:
            scoring = 'roc_auc'
        grid_search = GridSearchCV(self.pipeline, param_grid = param_grid,
                scoring = scoring,
                cv = cv,
                n_jobs = -1,
                fit_params = {'model__sample_weight': self.datasets.sample_weight})
        grid_search.fit(self.datasets.train_instances.getFeatures(),
                self.getSupervision(self.datasets.train_instances))
        self.conf.setBestValues(grid_search)
        self.pipeline.set_params(**self.conf.getBestValues())
        return cv