def ReliefF_compute_scores(inst, attr, nan_entries, num_attributes, mcmap, NN, headers, class_type, X, y, labels_std, data_type):
    """ Unique scoring procedure for ReliefF algorithm. Scoring based on k nearest hits and misses of current target instance. """
    scores = np.zeros(num_attributes)
    for feature_num in range(num_attributes):
        scores[feature_num] += compute_score(attr, mcmap, NN, feature_num, inst,
                                             nan_entries, headers, class_type, X, y, labels_std, data_type)
    return scores
def ReliefF_compute_scores ( inst , attr , nan_entries , num_attributes , mcmap , NN , headers , class_type , X , y , labels_std , data_type ) : scores = np . zeros ( num_attributes ) for feature_num in range ( num_attributes ) : scores [ feature_num ] += compute_score ( attr , mcmap , NN , feature_num , inst , nan_entries , headers , class_type , X , y , labels_std , data_type ) return scores
Unique scoring procedure for ReliefF algorithm. Scoring based on k nearest hits and misses of current target instance.