word2vec_bayes.py 文件源码

def predict_proba(self, docs):
        scores = np.hstack(cur_model.score(docs).reshape(-1, 1) for cur_model in self.models)
        if self.class_priors:
            scores += self.class_scores
        return np.exp(scores - logsumexp(scores, axis=1, keepdims=True))