sensitivityとかspecificityとか，classification_reportが計算してくれないやつを計算するためにTP, TN, FP, FNが必要

compute_clf.py

def compute_clf(confusion_matrix: numpy.ndarray, classes: list):
    """
    return TP, TN, FP, FN followed by the order of classes

    shape: (n_classes, 4)
    """
    ret = list()
    total = confusion_matrix.sum()

    for index, _class in enumerate(classes):
        row_sum = confusion_matrix[index, :].sum()
        column_sum = confusion_matrix[:, index].sum()

        tp = confusion_matrix[index, index]
        fn = row_sum - tp
        fp = column_sum - tp
        tn = total - row_sum - column_sum + tp

        ret.append([tp, tn, fp, fn])

    ret = numpy.asarray(ret)
    return ret