DocumentCode :
2637290
Title :
A Genetic Programming Ensemble Approach to Cancer Microarray Data Classification
Author :
Hengpraprohm, Supoj ; Chongstitvatana, Prabhas
Author_Institution :
Fac. of Sci. & Technol., Nakhon Pathom Rajabhat Univ., Nakhon Pathom
fYear :
2008
fDate :
18-20 June 2008
Firstpage :
340
Lastpage :
340
Abstract :
This paper presents a method for building an ensemble of classifiers for cancer microarray data. The proposed method exploits the advantage of a clustering technique, namely K-means clustering, combined with a feature selection technique, namely SNR feature selection. An evolutionary algorithm, namely Genetic Programming, is used to construct a number of classifiers which are assembled into an ensemble. The performance of the proposed method was tested on six cancer microarray data sets. The experimental results indicate that the proposed method yields a good prediction accuracy with a small standard deviation.
Keywords :
cancer; feature extraction; genetic algorithms; learning (artificial intelligence); medical computing; pattern classification; pattern clustering; K-means clustering; cancer microarray data classification; ensemble approach; evolutionary algorithm; feature selection; genetic programming; machine learning; Accuracy; Buildings; Cancer; Data analysis; Data engineering; Evolutionary computation; Genetic engineering; Genetic programming; Neoplasms; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
Conference_Location :
Dalian, Liaoning
Print_ISBN :
978-0-7695-3161-8
Electronic_ISBN :
978-0-7695-3161-8
Type :
conf
DOI :
10.1109/ICICIC.2008.35
Filename :
4603529
Link To Document :
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