dac.py 文件源码

def rank(self):
        '''
        Rank candidates according to trained model.
        '''
        for c in self.filtered_candidates:
            c.set_prob_features()

            # Only calculate prob if not in training mode
            if self.model.__class__.__name__ != 'Model':
                example = []
                for j in range(len(self.model.features)):
                    feature = getattr(c, self.model.features[j])
                    example.append(float(feature))
                c.prob = self.model.predict(example)

        self.ranked_candidates = sorted(self.filtered_candidates,
            key=attrgetter('prob'), reverse=True)