def classify_nb_one(self, frag):
        ## the prior is weird, but it works better this way, consistently
        probs = sbd_util.Counter([(label, self.feats[label, '<prior>']**4) for label in [0,1]])
        for label in probs:
            for feat, val in frag.features.items():
                key = (label, feat + '_' + val)
                if not self.feats in key: continue
                probs[label] *= self.feats[key]

        probs = sbd_util.normalize(probs)
        return probs[1]
dataset/ETHPy150Open daeilkim/refinery/refinery/lib/sbd.py/NB_Model.classify_nb_one/swapped operands of `in`