  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())))
            scores[df[features_r_uses].query(str(r)).index.values] += r.args[0]

        return scores

    def _get_complexity(self):
        check_is_fitted(self, [&#39;rules_without_feature_names_&#39;])
        return sum([len(rule.agg_dict) for rule in self.rules_without_feature_names_]) </code></pre>
</details>
<h3>Subclasses</h3>
<ul class="hlist">
<li><a t