output_profile_query = self._output_profile_transform(query)
weights = self.estimate_competence(output_profile_query.reshape(1, -1))
// If all weights is equals to zero, it means that no classifier was selected. Hence, use all of them
if all(weight == 0 for weight in weights):
weights = np.ones(self.n_classifiers, dtype=int)
votes = np.array([], dtype=int)
for clf_idx, clf in enumerate(self.pool_classifiers):
After Change
// If all weights is equals to zero, it means that no classifier was selected. Hence, use all of them with equal
// weights.
if np.sum(weights) == 0:
weights = np.ones(self.n_classifiers, dtype=int)
votes = np.array([], dtype=int)
for clf_idx, clf in enumerate(self.pool_classifiers):
