Filter-wrapper approach to feature selection using RST-DPSO for mining protein function

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper proposed a feature selection strategy based on rough set theory (RST) and discrete particle swarm optimization (DPSO) methods prior to classify protein function. RST is adopted in the first phase with the aim to eliminate the insignificant features and prepared the reduce features to the next phase. In the second phase, the reduced features are optimized using the new evolutionary computation method, DPSO. The optimum features from this two methods were mined using Support Vector Machine Classifier with the optimum RBF's kernel parameters. These methods have greatly reduced the features and achieved higher classification accuracy across the selected datasets compared to full features and RST alone. The results also demonstrate that the integration of RST and DPSO is capable of searching the optimal features for protein classification and applicable to different classification problem.

Original languageEnglish
Title of host publication2009 2nd Conference on Data Mining and Optimization, DMO 2009
Pages71-78
Number of pages8
DOIs
Publication statusPublished - 2009
Event2009 2nd Conference on Data Mining and Optimization, DMO 2009 - Bangi, Selangor
Duration: 27 Oct 200928 Oct 2009

Other

Other2009 2nd Conference on Data Mining and Optimization, DMO 2009
CityBangi, Selangor
Period27/10/0928/10/09

Fingerprint

Rough set theory
Particle swarm optimization (PSO)
Feature extraction
Proteins
Evolutionary algorithms
Support vector machines
Classifiers

Keywords

  • Data mining
  • Feature selection
  • Machine learning
  • Optimization
  • Particle swarm optimization

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Software

Cite this

Rahman, S. A., Abu Bakar, A., & Mohamed Hussein, Z. A. (2009). Filter-wrapper approach to feature selection using RST-DPSO for mining protein function. In 2009 2nd Conference on Data Mining and Optimization, DMO 2009 (pp. 71-78). [5341906] https://doi.org/10.1109/DMO.2009.5341906

Filter-wrapper approach to feature selection using RST-DPSO for mining protein function. / Rahman, Shuzlina Abdul; Abu Bakar, Azuraliza; Mohamed Hussein, Zeti Azura.

2009 2nd Conference on Data Mining and Optimization, DMO 2009. 2009. p. 71-78 5341906.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Rahman, SA, Abu Bakar, A & Mohamed Hussein, ZA 2009, Filter-wrapper approach to feature selection using RST-DPSO for mining protein function. in 2009 2nd Conference on Data Mining and Optimization, DMO 2009., 5341906, pp. 71-78, 2009 2nd Conference on Data Mining and Optimization, DMO 2009, Bangi, Selangor, 27/10/09. https://doi.org/10.1109/DMO.2009.5341906
Rahman, Shuzlina Abdul ; Abu Bakar, Azuraliza ; Mohamed Hussein, Zeti Azura. / Filter-wrapper approach to feature selection using RST-DPSO for mining protein function. 2009 2nd Conference on Data Mining and Optimization, DMO 2009. 2009. pp. 71-78
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