extra_trees_preproc_for_classification.py 文件源码

 复制代码def fit(self, X, Y, sample_weight=None):
        from sklearn.ensemble import ExtraTreesClassifier
        from sklearn.feature_selection import SelectFromModel

        num_features = X.shape[1]
        max_features = int(
            float(self.max_features) * (np.log(num_features) + 1))
        # Use at most half of the features
        max_features = max(1, min(int(X.shape[1] / 2), max_features))
        preprocessor = ExtraTreesClassifier(
            n_estimators=self.n_estimators, criterion=self.criterion,
            max_depth=self.max_depth, min_samples_split=self.min_samples_split,
            min_samples_leaf=self.min_samples_leaf, bootstrap=self.bootstrap,
            max_features=max_features, max_leaf_nodes=self.max_leaf_nodes,
            oob_score=self.oob_score, n_jobs=self.n_jobs, verbose=self.verbose,
            random_state=self.random_state, class_weight=self.class_weight
        )
        preprocessor.fit(X, Y, sample_weight=sample_weight)
        self.preprocessor = SelectFromModel(preprocessor, prefit=True)
        return self