or(&#34;X.shape[1] = %d should be equal to %d, the number of features at training time.&#34;
                             &#34; Please reshape your data.&#34;
                             % (X.shape[1], self.n_features_))

        df = pd.DataFrame(X, columns=self.feature_placeholders)
        selected_rules = self.rules_without_feature_names_

        scores = np.zeros(X.shape[0])
        for r in selected_rules: 
            features_r_uses = list(set(map(lambda x: x[0], r.agg_dict.keys())))
            s