tfidf_matrix = TfidfVectorizermax_df=095 min_df=2 max_features=n_features stop_words=english dtype=npfloat32fit_transformdocs_cleanda_model = gensimmodelsldamodelLdaModeltfidf_matrix num_topics=8 id2w

将n_features定义为一个整数值，例如：

n_features = 1000 # 设定为1000个最大特征值 tfidf_matrix = TfidfVectorizer(max_df=0.95, min_df=2, max_features=n_features, stop_words='english', dtype=np.float32).fit_transform(docs_clean) da_model = gensim.models.ldamodel.LdaModel(tfidf_matrix, num_topics=8, id2word=dict(enumerate(feature_names)), passes=10)