TextClassify issues

demo_bow.py 运行后准确率为1/8

1. debug发现test_predict的值全是'G_\xc2\xc3\xd3\xce\xbe\xb0\xb5\xe3'，全部分为了G类，求教为什么？ 2.而运行demo_tfidf.py 运行没问题，结果为accuracy is 0.912500，正好是你readme中使用demo_bow.py得到的结果，求教是不是哪里出错了？ 3. 如何让demo_tfidf.py 也可以保存分类器模型，每次只预测新样本，省略每次训练时间。 ps：环境python2.7 ，期待您的回复

wyk-qyf

bug fix: error of array in sklearn

ValueError: Expected 2D array, got 1D array instead: array=[ 0. 0. 0. ..., 0. 0. 0.]. Reshape your data either using array.reshape(-1, 1) if your data has a single feature...

yonglam

用python3训练tfidf时报错

for name in self.filenames: with open(join(name), 'r', 1000, 'utf-8') as f: tf_dict = dict() > > UnicodeDecodeError: 'utf-8' codec can't decode byte 0xb1 in position 0: invalid > > start...

snakecy