def predict_proba(self, X):
        """Return probability estimates for the test vector X.

        Parameters
        ----------
        X : array-like, shape = (n_samples, n_features)

        Returns
        -------
        C : array-like, shape = (n_samples, n_classes)
            Returns the probability of the samples for each class in
            the model. The columns correspond to the classes in sorted
            order, as they appear in the attribute `classes_`.
        """
        check_is_fitted(self, ["classes_", "n_classes_"])
        if self.n_classes_ > 2 and self.multi_class == "one_vs_one":
            raise ValueError("one_vs_one multi-class mode does not support "
                             "predicting probability estimates. Use "
                             "one_vs_rest mode instead.")
        X = check_array(X)
        return self.base_estimator_.predict_proba(X)
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/gaussian_process/gpc.py/GaussianProcessClassifier.predict_proba/original