feature_vector_space.py 文件源码

def transform(self):
        ## get common vocabulary
        tfidf = self._init_word_ngram_tfidf(self.ngram)
        tfidf.fit(list(self.obs_corpus) + list(self.target_corpus))
        vocabulary = tfidf.vocabulary_
        ## obs tfidf
        tfidf = self._init_word_ngram_tfidf(self.ngram, vocabulary)
        X_obs = tfidf.fit_transform(self.obs_corpus)
        ## targetument tfidf
        tfidf = self._init_word_ngram_tfidf(self.ngram, vocabulary)
        X_target = tfidf.fit_transform(self.target_corpus)
        ## svd
        svd = TruncatedSVD(n_components = self.svd_dim, 
                n_iter=self.svd_n_iter, random_state=config.RANDOM_SEED)
        svd.fit(scipy.sparse.vstack((X_obs, X_target)))
        X_obs = svd.transform(X_obs)
        X_target = svd.transform(X_target)
        ## cosine similarity
        sim = list(map(dist_utils._cosine_sim, X_obs, X_target))
        sim = np.asarray(sim).squeeze()
        return sim