sklearn简单实现TF-IDF

from sklearn.feature_extraction.text import CountVectorizer
#语料
corpus = [
    'This is the first document.',
    'This is the second second document.',
    'And the third one.',
    'Is this the first document?',
]
#将文本中的词语转换为词频矩阵
vectorizer = CountVectorizer()
#计算个词语出现的次数
X = vectorizer.fit_transform(corpus)
#获取词袋中所有文本关键词
word = vectorizer.get_feature_names()
print(word)
#查看词频结果
print(X.toarray())

from sklearn.feature_extraction.text import TfidfTransformer

#类调用
transformer = TfidfTransformer()
print