Research on Decision Tree Algorithm Based on Information Entropy

被引：0

作者：

Ning, Wei ^{[1
]}

Liang, Yon ^{[1
]}

Wang, Yuncheng ^{[1
]}

机构：

[1] Shandong Agr Univ, Coll Informat Sci & Engn, Tai An 271018, Shandong, Peoples R China

来源：

PROCEEDINGS OF THE 6TH CONFERENCE OF BIOMATHEMATICS, VOLS I AND II: ADVANCES ON BIOMATHEMATICS | 2008年

关键词：

decision tree; Classification algorithm; entropy; information gain; gain ratio;

D O I：

暂无

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Decision tree is an important learning method in machine learning and data mining,this paper discusses the method of choosing the best attribute based on information entropy. It analyzes the process and the characters of classification and the discovery knowledge based on decision tree about the application of decision tree on data mining. Through an instance the paper shows the procedure of selecting the decision attribute in detail,finally it pointer out the developing trends of decision tree.

引用

页码：568 / 572

页数：5

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