我正在尝试使用 NLTK 工具包对 Twitter 上的一部新电影进行一些情感分析。我遵循 NLTK 'movie_reviews' 示例,并构建了自己的 CategorizedPlaintextCorpusReader 对象。当我调用 nltk.classify.util.accuracy(classifier, testfeats) 时,问题就出现了。这是代码:
import os
import glob
import nltk.classify.util
from nltk.classify import NaiveBayesClassifier
from nltk.corpus import movie_reviews
def word_feats(words):
return dict([(word, True) for word in words])
negids = movie_reviews.fileids('neg')
posids = movie_reviews.fileids('pos')
negfeats = [(word_feats(movie_reviews.words(fileids=[f])), 'neg') for f in negids]
posfeats = [(word_feats(movie_reviews.words(fileids=[f])), 'pos') for f in posids]
trainfeats = negfeats + posfeats
# Building a custom Corpus Reader
tweets = nltk.corpus.reader.CategorizedPlaintextCorpusReader('./tweets', r'.*\.txt', cat_pattern=r'(.*)\.txt')
tweetsids = tweets.fileids()
testfeats = [(word_feats(tweets.words(fileids=[f]))) for f in tweetsids]
print 'Training the classifier'
classifier = NaiveBayesClassifier.train(trainfeats)
for tweet in tweetsids:
print tweet + ' : ' + classifier.classify(word_feats(tweets.words(tweetsids)))
classifier.show_most_informative_features()
print 'accuracy:', nltk.classify.util.accuracy(classifier, testfeats)
一切似乎都工作正常,直到到达最后一行。这就是我收到错误的时候:
>>> nltk.classify.util.accuracy(classifier, testfeats)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/lib/python2.7/dist-packages/nltk/classify/util.py", line 87, in accuracy
results = classifier.classify_many([fs for (fs,l) in gold])
ValueError: too many values to unpack
有人发现代码中有什么问题吗?
谢谢。
最佳答案
错误信息
File "/usr/lib/python2.7/dist-packages/nltk/classify/util.py", line 87, in accuracy
results = classifier.classify_many([fs for (fs,l) in gold])
ValueError: too many values to unpack
出现是因为 gold
中的项目无法解压缩为 2 元组,(fs,l)
:
[fs for (fs,l) in gold] # <-- The ValueError is raised here
如果gold
,您会得到同样的错误等于 [(1,2,3)]
,自 3 元组 (1,2,3)
无法解压缩为 2 元组 (fs,l)
:
In [74]: [fs for (fs,l) in [(1,2)]]
Out[74]: [1]
In [73]: [fs for (fs,l) in [(1,2,3)]]
ValueError: too many values to unpack
gold
可能被埋在 nltk.classify.util.accuracy
的实现中,但这暗示您的输入 classifier
或testfeats
“形状”错误。
分类器没有问题,因为调用 accuracy(classifier, trainfeats)
作品:
In [61]: print 'accuracy:', nltk.classify.util.accuracy(classifier, trainfeats)
accuracy: 0.9675
问题一定出在 testfeats
.
比较 trainfeats
与 testfeats
。
trainfeats[0]
是一个包含字典和分类的二元组:
In [63]: trainfeats[0]
Out[63]:
({u'!': True,
u'"': True,
u'&': True,
...
u'years': True,
u'you': True,
u'your': True},
'neg') # <--- Notice the classification, 'neg'
但是testfeats[0]
只是一个字典,word_feats(tweets.words(fileids=[f]))
:
testfeats = [(word_feats(tweets.words(fileids=[f]))) for f in tweetsids]
因此,要解决此问题,您需要定义 testfeats
看起来更像trainfeats
-- word_feats
返回的每个字典必须与分类配对。
关于python - NLTK精度: "ValueError: too many values to unpack",我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/31920199/