add idf

xuming06 · xuming06 · commit feb6ae75aa22 · 2018-07-04T21:26:48.000+08:00
diff --git a/11scikit-learn/idf.py b/11scikit-learn/idf.py
@@ -0,0 +1,27 @@
+# -*- coding: utf-8 -*-
+# Author: XuMing <xuming624@qq.com>
+# Brief: 
+
+from sklearn.feature_extraction.text import TfidfVectorizer
+
+corpus = ["I come to China to travel",
+          "This is a car polupar in China",
+          "I love tea and Apple ",
+          "The work is to write some papers in science"]
+
+vectorizer = TfidfVectorizer()
+
+tfidf = vectorizer.fit_transform(corpus)
+print(tfidf)
+print('vocab:')
+print(vectorizer.vocabulary_)
+word = vectorizer.get_feature_names()  # 获取词袋模型中的所有词语
+weight = tfidf.toarray()  # 将tf-idf矩阵抽取出来，元素a[i][j]表示j词在i类文本中的tf-idf权重
+for i in range(len(weight)):  # 打印每类文本的tf-idf词语权重，第一个for遍历所有文本，第二个for便利某一类文本下的词语权重
+    print(u"-------这里输出第", i, u"类文本的词语tf-idf权重------")
+    k_v = dict()
+    for j in range(len(word)):
+        print(word[j], weight[i][j])
+        k_v[word[j]] = weight[i][j]
+    sorts = sorted(k_v.items(), key=lambda d:d[1],reverse=True)
+    print(sorts[:5])
