An ensemble feature selection technique for cancer recognition

Bio-Medical Materials and Engineering

Volumn 24, Issue 1, 2014, Pages 1001-1008

  Xu, Jiucheng ^a,b   Sun, Lin ^a,b   Gao, Yunpeng ^a,b   Xu, Tianhe ^a,b  

^a HENAN NORMAL UNIVERSITY   (China)

^b Engineering Technology Research Center for Computing Intelligence and Data Mining   (China)

Author keywords

Feature selection; neighborhood mutual information; particle swarm optimization; support vector machine

Indexed keywords

CLASSIFICATION ACCURACY; ENSEMBLE FEATURE SELECTIONS; ENSEMBLE TECHNIQUES; EXPRESSION PROBLEM; GENE SELECTION ALGORITHMS; LEAVE-ONE-OUT CROSS VALIDATIONS; MUTUAL INFORMATIONS; REDUNDANT FEATURES;

BIOMEDICAL ENGINEERING; BIOTECHNOLOGY; DISEASES; FEATURE EXTRACTION; GENE EXPRESSION; PARTICLE SWARM OPTIMIZATION (PSO); STATISTICAL METHODS;

SUPPORT VECTOR MACHINES;

CANCER DIAGNOSIS; CONFERENCE PAPER; CORRELATION BASED FEATURE SELECTION; DIAGNOSTIC PROCEDURE; GENE EXPRESSION; MATHEMATICAL ANALYSIS; NEIGHBORHOOD MUTUAL INFORMATION; PARTICLE SWARM OPTIMIZATION; PATTERN RECOGNITION; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE; VALIDATION PROCESS;

FEATURE SELECTION; NEIGHBORHOOD MUTUAL INFORMATION; PARTICLE SWARM OPTIMIZATION; SUPPORT VECTOR MACHINE;

ALGORITHMS; BREAST NEOPLASMS; FEMALE; GENE EXPRESSION PROFILING; HUMANS; LEUKEMIA; REPRODUCIBILITY OF RESULTS; SOFTWARE; STOCHASTIC PROCESSES; SUPPORT VECTOR MACHINES;

EID: 84891045892     PISSN: 09592989     EISSN: None     Source Type: Journal    
DOI: 10.3233/BME-130897     Document Type: Conference Paper

References (18)

1. A. Sharma, S. Imto and S. Miyano, A top-r feature selection algorithm for microarray gene expression data, IEEE/ACM Transactions on Computational Biology and Bioinformatics 3 (2012), 754-764.
2. H. S. Shon, K. S. Yang C. W. Yoo and K. H. Ryu, Feature selection method using WF-LASSO for gene expression data analysis, in: The 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine, 2011, pp. 522-524.
3. Q. H. Hu, D. R. Yu and Z. X. Xie, Neighborhood classifiers, Expert Systems with Applications 34 (2008), 866-876.
4. L. Yu, Y. Han and M. E. Berens, Stable gene selection from microarray data via sample weighting, IEEE/ACM Transactions on Computational Biology and Bioinformatics 9 (2012), 262-272.
5. S. W. Zhang, D. S. Huang and S. L. Wang, A method of tumor classification based on wavelet packet transforms and neighborhood rough set, Computers in Biology and Medicine 40 (2010), 430-437.
6. B. Li, C. H. Zheng, D. S. Huang, L. Zhang and K. Han, Gene expression data classification using locally linear discriminant embedding, Computers in Biology and Medicine 40 (2010), 802-810.
7. J. P. Huang, H. Fang and X. H. Fan, Decision forest for classification of gene expression data, Computers in Biology and Medicine 40 (2010), 698-704.
8. Z. X. Zhu, Y. S. Ong and M. Dash, Wrapper-filter feature selection algorithm using a memetic framework, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 37 (2007), 70-76.
9. M. A. Hall, Correlation-based feature subset selection for machine learning, PhD thesis, Department of Computer Science, University of Waikato, Haimlton, New Zealand, 1999.
10. H. Liu and L. Yu, Toward integrating feature selection algorithm for classification and clustering, IEEE Transactions on Knowledge and Data Engineering 17 (2005), 491-502.
11. Q. H. Hu, W. Pan, S. An, P. J. Ma and J. M. Wei, An efficient gene selection technique for cancer recognition based on neighborhood mutual information, International Journal of Machine Learning and Cybernetics 1 (2010), 63-74.
12. X. Y. Wang, J. Yang, X. L. Teng, W. J. Xia and R. Jensen, Feature selection based on rough sets and particle swarm optimization, Pattern Recognition Letters 28 (2007), 459-471.
13. C. M. Perou, T. Srlie, M. B. Eisen, et al. , Molecular portraits of human breast tumours, Nature 406 (2000), 747-752.
14. A. A. Alizadeh, M. B. Eisen, R. E. Davis, et al. , Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling, Nature 403 (2000), 503-511.
15. J. Liu, H. Iba and M. Ishizuka, Selecting informative genes with parallel genetic algorithms in tissue classification, Genome Informatics 12 (2001), 14-23.
16. S. A. Armstrong, J. E. Staunton, L. B. Silverman, et al. , MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia, Nature Genetics 30 (2000), 41-47.
17. D. G. Beer, S. L. R. Kardia, C. C. Huang, et al. , Gene-expression profiles predict survival of patients with lung adenocarcinoma, Nature Medicine 8 (2002), 816-824.
18. J. Khan, J. S. Wei, M. Ringner, L. H. Saal, et al. , Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks, Nature Medicine 7 (2001), 673-679.