b2afdded85cbe4560baf56c08feae93aab3bc508,deslib/dcs/rank.py,Rank,estimate_competence,#Rank#,87

Before Change

                      The competence level estimated for each base classifier and test example
        
        _, idx_neighbors = self._get_region_competence(query)
        idx_neighbors = np.atleast_2d(idx_neighbors)
        results_neighbors = self.processed_dsel[idx_neighbors, :]

        // Get the shape of the vector in order to know the number of samples, base classifiers and neighbors considered.
        shape = results_neighbors.shape

        // add an row with zero for the case where the base classifier correctly classifies the whole neighborhood.
        // That way the search will always find a zero after comparing to self.K + 1
        addition = np.zeros((shape[0], shape[2]))
        results_neighbors = np.insert(results_neighbors, shape[1], addition, axis=1)
        competences = np.argmax(results_neighbors == 0, axis=1)

        return competences

After Change

        results_neighbors = np.insert(results_neighbors, shape[1], addition, axis=1)
        competences = np.argmax(results_neighbors == 0, axis=1)

        return competences.astype(np.float32)

Instances