search_light.py 文件源码

def fit(self, X, y):
        """Fit a series of independent estimators to the dataset.

        Parameters
        ----------
        X : array, shape (n_samples, n_features, n_estimators)
            The training input samples. For each data slice, a clone estimator
            is fitted independently.
        y : array, shape (n_samples,)
            The target values.

        Returns
        -------
        self : object
            Return self.
        """
        self._check_Xy(X, y)
        self.estimators_ = list()
        # For fitting, the parallelization is across estimators.
        parallel, p_func, n_jobs = parallel_func(_sl_fit, self.n_jobs)
        estimators = parallel(
            p_func(self.base_estimator, split, y)
            for split in np.array_split(X, n_jobs, axis=-1))
        self.estimators_ = np.concatenate(estimators, 0)
        return self