DocumentCode :
3324754
Title :
Research on new data mining method based on hybrid genetic algorithm
Author :
Lianmei, Zhang ; Xingjun, Jiang
Author_Institution :
Comput. Sch., Wuhan Univ., Wuhan, China
Volume :
1
fYear :
2010
fDate :
5-7 May 2010
Firstpage :
462
Lastpage :
465
Abstract :
For classification problems in data mining based on the thought of combination classification method, this paper proposes a combination classification method of multiple decision trees, which was based on genetic algorithm. In the proposed combination classification method, multiple decision trees that adopt the method of probability measurement level output are parallel combined. Then genetic algorithm is used for the optimization of connection weight matrix in combination algorithm. Further more, two sets of simulation experiment data are used to test and evaluate the proposed combination classification method. Results of the experiments indicate that the proposed combination classification method has higher classification accuracy level than single decision tree. Moreover, it optimizes classification rules and sustains good interpretability for classification results.
Keywords :
data mining; decision trees; genetic algorithms; classification accuracy; combination classification method; connection weight matrix; data mining method; decision tree; hybrid genetic algorithm; probability measurement level output; Automatic control; Bayesian methods; Classification tree analysis; Communication system control; Data mining; Decision trees; Genetic algorithms; Radio control; Testing; Voting; combination method; formatting; genetic algorithm; insert (key words) data mining; multiple decision trees; style; styling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Communication Control and Automation (3CA), 2010 International Symposium on
Conference_Location :
Tainan
Print_ISBN :
978-1-4244-5565-2
Type :
conf
DOI :
10.1109/3CA.2010.5533761
Filename :
5533761
Link To Document :
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