我正在尝试使用NLTK进行python训练我自己的语料库以进行情绪分析。我有两个文本文件:一个有25K正面推文,每行分开,另一个是25K负推文。
I use this Stackoverflow article, method 2
当我运行此代码来创建语料库时:
import string
from itertools import chain
from nltk.corpus import stopwords
from nltk.probability import FreqDist
from nltk.classify import NaiveBayesClassifier as nbc
from nltk.corpus import CategorizedPlaintextCorpusReader
import nltk
mydir = 'C:\Users\gerbuiker\Desktop\Sentiment Analyse\my_movie_reviews'
mr = CategorizedPlaintextCorpusReader(mydir, r'(?!\.).*\.txt', cat_pattern=r'(neg|pos)/.*', encoding='ascii')
stop = stopwords.words('english')
documents = [([w for w in mr.words(i) if w.lower() not in stop and w.lower() not in string.punctuation], i.split('/')[0]) for i in mr.fileids()]
word_features = FreqDist(chain(*[i for i,j in documents]))
word_features = word_features.keys()[:100]
numtrain = int(len(documents) * 90 / 100)
train_set = [({i:(i in tokens) for i in word_features}, tag) for tokens,tag in documents[:numtrain]]
test_set = [({i:(i in tokens) for i in word_features}, tag) for tokens,tag in documents[numtrain:]]
classifier = nbc.train(train_set)
print nltk.classify.accuracy(classifier, test_set)
classifier.show_most_informative_features(5)
我收到错误消息:
C:\Users\gerbuiker\Anaconda\python.exe "C:/Users/gerbuiker/Desktop/Sentiment Analyse/CORPUS_POS_NEG/CreateCorpus.py"
Traceback (most recent call last):
File "C:/Users/gerbuiker/Desktop/Sentiment Analyse/CORPUS_POS_NEG/CreateCorpus.py", line 23, in <module>
documents = [([w for w in mr.words(i) if w.lower() not in stop and w.lower() not in string.punctuation], i.split('/')[0]) for i in mr.fileids()]
File "C:\Users\gerbuiker\AppData\Roaming\Python\Python27\site-packages\nltk\corpus\reader\util.py", line 336, in iterate_from
assert self._len is not None
AssertionError
Process finished with exit code 1
有谁知道如何解决这个问题?
答案 0 :(得分:1)
我不是100%肯定,因为我现在不在Windows机器上进行测试,但我认为可能会引起你注意的是@alvas原始示例中的路径斜线方向与您的适应窗户。
具体来说,您使用<div class="box3">
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margin-top:3px;
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float:left;
width:65%;
background:#707070;
height:300px;
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,而他的示例使用'C:\Users\gerbuiker\Desktop\Sentiment Analyse\my_movie_reviews'
。在大多数情况下,这很好,但是你试图重新使用他的'/home/alvas/my_movie_reviews'
正则表达式:cat_pattern
,它将匹配路径中的斜杠,但拒绝你的路径中的斜杠。