def predict_proba(self, X: np.ndarray, batch_size: int = 1000 ) -> np.ndarray: new_X = np.ones((X.shape[0], 1)) probas = super(MyDummyClassifier, self).predict_proba(new_X) probas = convert_multioutput_multiclass_to_multilabel(probas).astype( np.float32) return probas
def predict_proba(self, X): if self.estimator is None: raise NotImplementedError() probas = self.estimator.predict_proba(X) probas = convert_multioutput_multiclass_to_multilabel(probas) return probas
def predict_proba(self, X, batch_size=1000): new_X = np.ones((X.shape[0], 1)) probas = super(MyDummyClassifier, self).predict_proba(new_X) probas = convert_multioutput_multiclass_to_multilabel(probas).astype( np.float32) return probas