我正在尝试使用scikit训练一些文本数据。相同的代码正在其他电脑上使用,没有任何错误,但在我的系统上,它给出了错误:
File "/root/Desktop/karim/svn/questo-anso/v5/trials/classify/domain_detection_final/test_classifier_temp.py", line 130, in trainClassifier
X_train = self.vectorizer.fit_transform(self.data_train.data)
File "/root/Desktop/karim/software/scikit-learn-0.15.1/sklearn/feature_extraction/text.py", line 1270, in fit_transform
X = super(TfidfVectorizer, self).fit_transform(raw_documents)
File "/root/Desktop/karim/software/scikit-learn-0.15.1/sklearn/feature_extraction/text.py", line 808, in fit_transform
vocabulary, X = self._count_vocab(raw_documents, self.fixed_vocabulary)
File "/root/Desktop/karim/software/scikit-learn-0.15.1/sklearn/feature_extraction/text.py", line 741, in _count_vocab
for feature in analyze(doc):
File "/root/Desktop/karim/software/scikit-learn-0.15.1/sklearn/feature_extraction/text.py", line 233, in <lambda>
tokenize(preprocess(self.decode(doc))), stop_words)
File "/root/Desktop/karim/software/scikit-learn-0.15.1/sklearn/feature_extraction/text.py", line 111, in decode
doc = doc.decode(self.encoding, self.decode_error)
File "/usr/lib/python2.7/encodings/utf_8.py", line 16, in decode
return codecs.utf_8_decode(input, errors, True)
UnicodeDecodeError: 'utf8' codec can't decode byte 0xba in position 1266: invalid start byte
我已经检查了类似的线程,但没有任何帮助。
更新:
self.data_train = self.fetch_data(cache, subset='train')
if not os.path.exists(self.root_dir+"/autocreated/vectorizer.txt"):
self.vectorizer = TfidfVectorizer(sublinear_tf=True, max_df=0.5,
stop_words='english')
start_time = time()
print("Transforming the dataset")
X_train = self.vectorizer.fit_transform(self.data_train.data) // Error is here
joblib.dump(self.vectorizer, self.root_dir+"/autocreated/vectorizer.txt")
您的文件实际上是用ISO-8869-1编码的,而不是UTF-8。您需要对其进行正确解码,然后才能再次对其进行编码。
0xBA是ISO-8869-1中的数字符号(º
)。
处理训练数据时出现问题。解决我问题的一件事是ignoring error
使用decode_error='ignore'
,可能还有其他一些解决方案。
self.vectorizer = TfidfVectorizer(sublinear_tf=True, max_df=0.5,stop_words='english',decode_error='ignore')