Method predict_proba

sklearn/calibration.py:509–536

Calibrated probabilities of classification. This function returns calibrated probabilities of classification according to each class on an array of test vectors X. Parameters ---------- X : array-like of shape (n_samples, n_features) The samples,

(self, X)

        return self

    def predict_proba(self, X):
        """Calibrated probabilities of classification.

        This function returns calibrated probabilities of classification
        according to each class on an array of test vectors X.

        Parameters
        ----------
        X : array-like of shape (n_samples, n_features)
            The samples, as accepted by `estimator.predict_proba`.

        Returns
        -------
        C : ndarray of shape (n_samples, n_classes)
            The predicted probas.
        """
        check_is_fitted(self)
        # Compute the arithmetic mean of the predictions of the calibrated
        # classifiers
        xp, _, device_ = get_namespace_and_device(X)
        mean_proba = xp.zeros((_num_samples(X), self.classes_.shape[0]), device=device_)
        for calibrated_classifier in self.calibrated_classifiers_:
            proba = calibrated_classifier.predict_proba(X)
            mean_proba += proba

        mean_proba /= len(self.calibrated_classifiers_)

        return mean_proba

    def predict(self, X):
        """Predict the target of new samples.