DocumentCode
1946236
Title
Notice of Retraction
Review of decision trees
Author
Xie Niuniu ; Liu Yuxun
Author_Institution
Coll. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou, China
Volume
5
fYear
2010
fDate
9-11 July 2010
Firstpage
105
Lastpage
109
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
The decision tree algorithm is a hot point in the field of data mining, which is usually used to form classifiers and prediction models. In practice, it has a wide application. This paper describes the decision tree technology and its development process, focuses on typical decision tree algorithms, analyzes their advantages and disadvantages, compares several algorithms, and finally discusses the development of the decision tree algorithm in the future.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
The decision tree algorithm is a hot point in the field of data mining, which is usually used to form classifiers and prediction models. In practice, it has a wide application. This paper describes the decision tree technology and its development process, focuses on typical decision tree algorithms, analyzes their advantages and disadvantages, compares several algorithms, and finally discusses the development of the decision tree algorithm in the future.
Keywords
data mining; decision trees; pattern classification; classifier model; data mining; decision tree; prediction model; Classification algorithms; Classification tree analysis; Complexity theory; Scalability; Silicon; classification; data mining; decision tree; test attribute;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-5537-9
Type
conf
DOI
10.1109/ICCSIT.2010.5564437
Filename
5564437
Link To Document