7704337b2f1ef68952848b1e622e62497e0fe0b8,pythonds/base.py,DS,predict_proba_ensemble,#DS#Any#Any#Any#,375

Before Change

        // if indices is empty (no classifier is selected, use all of them)
        if len(indices) == 0:
            indices = list(range(self.n_classifiers))
            weights = np.ones(self.n_classifiers)/self.n_classifiers

        proba = np.zeros(self.n_classes)

        for idx in indices:

After Change

        
        ensemble_size = len(indices)
        if weights is not None:
            if weights.size != ensemble_size:
                raise ValueError("The size of the weights vector should be equals to the size of the ensemble!")

        // if indices is empty (no classifier is selected, use all of them)
        if ensemble_size == 0:
            indices = list(range(self.n_classifiers))

        proba = np.zeros((1, self.n_classes))

Instances