我在scikit-learn中使用TfidfVectorizor函数 . 我试图使用“use_idf = True”包含tf-idf元素 . 在文档中，它说在此之后，result.idf_应该返回我的idf权重的数组和形状，但我得到“无” . 以下是我的输入和输出 . （我最终试图判断min_df和max_df如何影响我的结果，所以它们现在只是随机值） .
tester =TfidfVectorizer(docs_train, min_df=.2, max_df=.8, use_idf=True)
print tester
TfidfVectorizer(analyzer=u'word', binary=False, charset=None,
charset_error=None, decode_error=u'strict',
dtype=<type 'numpy.int64'>, encoding=u'utf-8',
input=["today , war became a reality to me after seeing a screening of saving priivate ryan . \nsteve spielberg goes beyond reality with his latest production . \nthe audience is tossed about the theatre witnessing the horror of war . \nplease keep the kids home as the r rating is for reality . \nto...esting motif out of the ubiquitous palmetto bugs-but nothing can freshen up this stale script . \n'],
lowercase=True, max_df=0.8, max_features=None, min_df=0.2,
ngram_range=(1, 1), norm=u'l2', preprocessor=None, smooth_idf=True,
stop_words=None, strip_accents=None, sublinear_tf=False,
token_pattern=u'(?u)\\b\\w\\w+\\b', tokenizer=None, use_idf=True,
vocabulary=None)
print tester.idf_
None
1 回答
你还没有为矢量化器提供任何数据 . 您应该使用
fit或fit_transform这样做 .