reuters_classifier.py 文件源码

def tokenize(text):

    min_length = 3
    words = map(lambda word: word.lower(), word_tokenize(text))
    words = [word for word in words if word not in cachedStopWords]
    tokens = (list(map(lambda token: PorterStemmer().stem(token), words)))
    p = re.compile('[a-zA-Z]+')
    filtered_tokens = list(filter(lambda token: p.match(token) and len(token) >= min_length, tokens))
    return filtered_tokens