def _score_macro_average(self, n_classes):
        """
        Compute the macro average scores for the ROCAUC curves.
        """
        # Gather all FPRs
        all_fpr = np.unique(np.concatenate([self.fpr[i] for i in range(n_classes)]))
        avg_tpr = np.zeros_like(all_fpr)

        # Compute the averages per class
        for i in range(n_classes):
            avg_tpr += interp(all_fpr, self.fpr[i], self.tpr[i])

        # Finalize the average
        avg_tpr /= n_classes

        # Store the macro averages
        self.fpr[MACRO] = all_fpr
        self.tpr[MACRO] = avg_tpr
        self.roc_auc[MACRO] = auc(self.fpr[MACRO], self.tpr[MACRO])