f(self.threshold_alpha_veritas)

        if self.VERBOSE:
            print(self.veritas_model)
        
        # Using test data to infer the decision threshold for the upper threshold
        if self.target_label:
            df_test = self.data.loc[[x for x in self.data.index.values if x not in self.training_index], :]
            featurenames = df_test.drop(self.target_label, axis=1, errors=&#39;ignore&#39;).columns
            labels = df_test[self.target_label].values.astype(int)

            df_test