sklearn CountVectorizer\TfidfVectorizer\TfidfTransformer函数详解

• sklearn CountVectorizer函数详解

from sklearn.feature_extraction.text import CountVectorizer

texts=["dog cat fish","dog cat cat","fish bird", 'bird']
cv = CountVectorizer()
cv_fit=cv.fit_transform(texts)

print(cv.get_feature_names())
print(cv_fit.toarray())
print(cv_fit)

• 返回的结果为稀疏矩阵

['bird', 'cat', 'dog', 'fish']
[[0 1 1 1]
 [0 2 1 0]
 [1 0 0 1]
 [1 0 0 0]]
  (0, 3)    1
  (