将NLTK停用词与scikit-learn的TfidfVectorizer一起使用时的Unicode警告 [英] Unicode Warning when using NLTK stopwords with TfidfVectorizer of scikit-learn

问题描述

我正在尝试使用scikit-learn中的Tf-idf Vectorizer，并使用NLTK中的西班牙语停用词:

I am trying to use the Tf-idf Vectorizer from scikit-learn, using the spanish stopwords from NLTK:

from nltk.corpus import stopwords

vectorizer = TfidfVectorizer(stop_words=stopwords.words("spanish"))

问题是我收到以下警告:

The problem is that I get the following warning:

/home/---/.virtualenvs/thesis/local/lib/python2.7/site-packages/sklearn/feature_extraction/text.py:122: UnicodeWarning: Unicode equal comparison failed to convert both arguments to Unicode - interpreting them as being unequal
tokens = [w for w in tokens if w not in stop_words]

有解决此问题的简便方法吗?

Is there an easy way to solve this issue?

推荐答案

实际上，这个问题比我想象的要容易解决.这里的问题是NLTK不返回unicode对象，而是str对象.因此，在使用它们之前，我需要从utf-8对其进行解码:

Actually the problem was more easy to solve than I thought. The issue here is that NLTK does not return unicode object, but str objects. So I needed to decode them from utf-8 before using them:

stopwords = [word.decode('utf-8') for word in stopwords.words('spanish')]

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