AttributeError : lower not found

Question

我在做文档分类，准确率高达 76%。在预测文档类别时，我做了以下一个

doc_clf.predict(tf_idf.transform((count_vect.transform([r'document']))))

我收到以下错误：

File "/usr/local/lib/python3.5/dist- packages/sklearn/utils/metaestimators.py", line 115, in <lambda>
  out = lambda *args, **kwargs: self.fn(obj, *args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/sklearn/pipeline.py", line 306, in predict
  Xt = transform.transform(Xt)
File "/usr/local/lib/python3.5/dist-packages/sklearn/feature_extraction/text.py", line 923, in transform
  _, X = self._count_vocab(raw_documents, fixed_vocab=True)
File "/usr/local/lib/python3.5/dist-packages/sklearn/feature_extraction/text.py", line 792, in _count_vocab
  for feature in analyze(doc):
File "/usr/local/lib/python3.5/dist-packages/sklearn/feature_extraction/text.py", line 266, in <lambda>
  tokenize(preprocess(self.decode(doc))), stop_words)
File "/usr/local/lib/python3.5/dist-packages/sklearn/feature_extraction/text.py", line 232, in <lambda>
  return lambda x: strip_accents(x.lower())
File "/usr/local/lib/python3.5/dist-packages/scipy/sparse/base.py", line 647, in __getattr__
  raise AttributeError(attr + " not found")

我该如何纠正这个错误？还有其他进一步提高准确性的方法吗？

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Answer 1

在您的代码中，doc_clf 是一个管道。因此 tf_idf.transform() 和 count_vect.transform() 将由管道自动处理。

你应该只调用

category = doc_clf.predict([r'document'])

当这个文档通过管道时，它会被 CountVectorizer 和 TfidfTransformer 自动转换。

AttributeError : lower not found

AttributeError : lower not found

python-3.x

scikit-learn

stochastic