(self, X)
return self.unordered_predict(X)
Following an unordered set of rules, for each instance, all
        rules are tried and those that fire are collected. If a clash
        occurs, class probabilities (predictions) of all collected rules
        are summed and weighted.

        Parameters
        ----------
        X : ndarray
            Classify this data.

        Returns
        -------
        res : ndarray, float
            Probabilistic classification.
Following an unordered set of rules, for each instance, all
        rules are tried and those that fire are collected. If a clash
        occurs, class probabilities (predictions) of all collected rules
        are summed and weighted.
Following an unordered set of rules for each instance all rules are tried and those that fire are collected . If a clash occurs class probabilities ( predictions ) of all collected rules are summed and weighted .
def predict(self, X):
        """
        Following an unordered set of rules, for each instance, all
        rules are tried and those that fire are collected. If a clash
        occurs, class probabilities (predictions) of all collected rules
        are summed and weighted.

        Parameters
        ----------
        X : ndarray
            Classify this data.

        Returns
        -------
        res : ndarray, float
            Probabilistic classification.
        """
        return self.unordered_predict(X)
def predict ( self , X ) : return self . unordered_predict ( X )