Method _predict

textmatch/models/text_embedding/bow_sklearn.py:116–120

(self, words)

        self._gen_dic(word_list)
    
    def _predict(self, words):
        tf_idf_embedding = self.vectorizer.transform(self._seg_word([words]))
        tf_idf_embedding = tf_idf_embedding.toarray().sum(axis=0)
        # print ('>>>>', tf_idf_embedding[np.newaxis, :]) 
        return tf_idf_embedding[np.newaxis, :].astype(float)
    
    def predict(self, words):
        pre = self._normalize( self._predict(words) )