def __confusion_matrix(self, length, labels, prediction):
        TP = 0
        FP = 0
        FN = 0
        correct_preds = []
        for pred in prediction:
            if pred in labels:
                TP += 1
                correct_preds.append(pred)
            else:
                FP += 1
        for label in labels:
            if label not in prediction:
                FN += 1
        TN = length - TP - FP - FN
        return FN, FP, TP, TN, correct_preds