TfidfVectorizer统计词频
作者:互联网
from sklearn.feature_extraction.text import TfidfVectorizer
import jieba
# text = ['This is the first document.', 'This is the second second document.', 'And the third one.',
# 'Is this the first document?', ]
#
# tf = TfidfVectorizer(min_df=1)
#
# X = tf.fit_transform(text)
# names = tf.get_feature_names()
# print(names)
# print(X.toarray())
text = '今天天气真好,我要去北京天安门玩,要去景山攻牙之后,玩完大明劫'
# 进行结巴分词,精确模式
text_list = jieba.cut(text, cut_all=False)
text_list = ",".join(text_list)
context = []
context.append(text_list)
print(context)
tf = TfidfVectorizer(min_df=1)
X = tf.fit_transform(context)
names = tf.get_feature_names()
print(names)
print(X.toarray())
标签:text,list,print,TfidfVectorizer,词频,names,tf,统计 来源: https://blog.csdn.net/YPL_ZML/article/details/93906460