通过sklearn使用tf-idf提取英文关键词

Demo1

TfidfTransformer + CountVectorizer = TfidfVectorizer

from sklearn.feature_extraction.text import TfidfVectorizer, TfidfTransformer
 
corpus = [
       'This This is the first document.',
      'This This is the second second document.',
      'And the third one.',
      'Is this the first document?',
]
 
tfidf_model = TfidfVectorizer()
 
tfidf_matrix = tfidf_model.fit_transform(corpus)
 
word_dict = tfidf_model.get_feature_names()
 
print(word_dict)
 
print(tfidf_matrix)

['and', 'document', 'first', 'is', 'one', 'second', 'the', 'third', 'this']
(0, 1) 0.3493402123185688
(0, 2) 0.431504661587479
(0, 6) 0.2856085141790751
(0, 3) 0.3493402123185688
(0, 8) 0.6986804246371376
(1, 5) 0.7717016211057586
(1, 1) 0.24628357422338598
(1, 6) 0.20135295972313796
(1, 3) 0.24628357422338598
(1, 8) 0.49256714844677196
(2, 4) 0.5528053199908667
(2, 7) 0.5528053199908667
(2, 0) 0.5528053199908667
(2, 6) 0.2884767487500274
(3, 1) 0.4387767428592343
(3, 2) 0.5419765697264572
(3, 6) 0.35872873824808993
(3, 3) 0.4387767428592343
(3, 8) 0.4387767428592343

参数设置

关于参数：

• input：string{'filename', 'file', 'content'}