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我是python新手,需要帮助!我正在练习python NLTK文本分类.以下是我在http://www.laurentluce.com/posts/twitter-sentiment-analysis-using-python-and-nltk/上练习的代码示例

我试过这个

from nltk import bigrams
from nltk.probability import ELEProbDist, FreqDist
from nltk import NaiveBayesClassifier
from collections import defaultdict

train_samples = {}

with file ('positive.txt', 'rt') as f:
   for line in f.readlines():
       train_samples[line]='pos'

with file ('negative.txt', 'rt') as d:
   for line in d.readlines():
       train_samples[line]='neg'

f=open("test.txt", "r")
test_samples=f.readlines()

def bigramReturner(text):
    tweetString = text.lower()
    bigramFeatureVector = {}
    for item in bigrams(tweetString.split()):
        bigramFeatureVector.append(' '.join(item))
    return bigramFeatureVector

def get_labeled_features(samples):
    word_freqs = {}
    for text, label in train_samples.items():
        tokens = text.split()
        for …