extra_trees.py 文件源码

def iterative_fit(self, X, y, n_iter=1, refit=False):
        from sklearn.ensemble import ExtraTreesRegressor as ETR

        if refit:
            self.estimator = None

        if self.estimator is None:
            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))
            self.estimator = ETR(
                n_estimators=0, 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,
                warm_start=True
            )
        tmp = self.estimator  # TODO copy ?
        tmp.n_estimators += n_iter
        tmp.fit(X, y,)
        self.estimator = tmp
        return self