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()