def source_competence(self): """Calculates the source of competence using the Minimum Difference method. The source of competence C_src at the validation point xk calculated by the Minimum Difference between the supports obtained to the correct class and the support obtained by the other classes Returns ---------- C_src : array of shape = [n_samples, n_classifiers] The competence source for each base classifier at each data point. """ C_src = np.zeros((self.n_samples, self.n_classifiers)) for clf_index in range(self.n_classifiers): supports = self._get_scores_dsel(clf_index) C_src[:, clf_index] = min_difference(supports, self.DSEL_target) return C_src
def test_min_difference(supports, idx_correct_label, expected): result = min_difference(supports, idx_correct_label) assert np.isclose(result, expected, atol=0.01).all()