Python nltk.DecisionTreeClassifier.train不'；行不通

我正在尝试运行以下代码，该代码在以下书籍章节中作为示例提供：[参见1.4词性标记]

import nltk
from nltk.corpus import brown

#
suffix_fdist = nltk.FreqDist()
for word in brown.words():
    word = word.lower()
    suffix_fdist[word[-1:]] += 1
    suffix_fdist[word[-2:]] += 1
    suffix_fdist[word[-3:]] += 1

common_suffixes = [suffix for (suffix,count) in suffix_fdist.most_common(100)]
print(common_suffixes)

def pos_features(word):
    features={}
    for suffix in common_suffixes:
        features['endswith({})'.format(suffix)] = word.lower().endswith(suffix)
    return features

tagged_words = brown.tagged_words(categories='news')
featuresets = [(pos_features(n), g) for (n,g) in tagged_words]

size = int(len(featuresets)*0.1)
train_set, test_set = featuresets[size:], featuresets[:size]

classifier = nltk.DecisionTreeClassifier.train(train_set)
nltk.classify.accuracy(classifier, test_set)

当我运行代码时，空闲似乎进入无限循环。问题似乎发生在nltk.DecisionTreeClassifier.trai方法调用中。如果您知道为什么会发生这种情况，以及我将如何着手解决它，我们将不胜感激

迈克