'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_`.'

def predict_proba(self, X):

    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)
