python - Python增量

我正在编写一个程序，它将接受文本作为输入。

程序的值“ tone”从0开始。
当看到该文本中的一个单词（也位于单词“ posfeats”列表中）时，色调会以+1递增。
当看到该文本中的单词（也包含单词“ neffeats”）时，该音调将以-1递增。

但是，无论我输入什么输入文本，我的代码都会为值“ tone”返回0。我觉得这是由于我的Python编程错误而不是我的算法引起的。

这是代码：

import nltk.classify.util
from nltk.classify import NaiveBayesClassifier
from nltk.corpus import movie_reviews #importing two corpora, movie_reviews and stopwords
from nltk.corpus import stopwords

def word_feats(words):
stops = dict([(word, True) for word in stopwords.words('english')]) #English stopwords
features = dict([(word, True) for word in words if word not in stops])#features minus stopwords
return features

def compare(words, negfeats, posfeats):
sentiment=0
for word in words:
    if word in negfeats:
        sentiment -= 1
    if word in posfeats:
        sentiment += 1
return sentiment


negReviews = reviews.fileids('neg')
posReviews = reviews.fileids('pos')

negfeats = [(word_feats(reviews.words(fileids=[f])), 'neg') for f in negReviews]
posfeats = [(word_feats(reviews.words(fileids=[f])), 'pos') for f in posReviews]

opinion = raw_input("Why don't you tell me about a movie you watched recently?\n\n")
tone = compare(opinion.split(), negfeats, posfeats)
print(str(tone)) #THIS KEEPS RETURNING 0

最佳答案

negfeats = [(word_feats(reviews.words(fileids=[f])), 'neg') for f in negReviews]
posfeats = [(word_feats(reviews.words(fileids=[f])), 'pos') for f in posReviews]

您是要在这里打dict电话吗？ negfeats和posfeats是(word, 'neg')和(word, 'pos')元组的列表。 compare将在这些列表中搜索单词，但找不到任何单词，因为单词嵌套在元组中。当然，最好将set用于没有重复的无序集合。

关于python - Python增量，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/21035950/