A novel ensemble selection method for cancer diagnosis using microarray datasets

Mohammed A. Gaafar, Noha Yousri, Mohamed A. Ismail

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

5 Citations (Scopus)

Abstract

Ensembles of classifiers have recently proved their efficiency in cancer diagnosis based on microarray datasets. The main performance indicators, namely, accuracy and diversity, present the main focus of study when designing an ensemble. One other important performance indicator is classification robustness. In an attempt to improve the performance of an ensemble, the proposed algorithm presents a variation concerning the diversity method used. The proposed algorithm attempts to enhance the robustness of the classification by searching for an ensemble of diverse classifiers. Also, a comparison of the different diversity methods is presented in order to study their impact on the robustness of the classification. The experiments performed show that the diversity method used in the proposed algorithm outperforms the other diversity methods in terms of accuracy and robustness.

Original languageEnglish
Title of host publicationIEEE 12th International Conference on BioInformatics and BioEngineering, BIBE 2012
Pages368-373
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2012
Externally publishedYes
Event12th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2012 - Larnaca, Cyprus
Duration: 11 Nov 201213 Nov 2012

Other

Other12th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2012
CountryCyprus
CityLarnaca
Period11/11/1213/11/12

Fingerprint

Microarrays
Classifiers
Experiments

Keywords

  • Cancer Classification
  • Ensemble Selection
  • Gene Selection
  • Microarray Classification

ASJC Scopus subject areas

  • Bioengineering
  • Biomedical Engineering

Cite this

Gaafar, M. A., Yousri, N., & Ismail, M. A. (2012). A novel ensemble selection method for cancer diagnosis using microarray datasets. In IEEE 12th International Conference on BioInformatics and BioEngineering, BIBE 2012 (pp. 368-373). [6399652] https://doi.org/10.1109/BIBE.2012.6399652

A novel ensemble selection method for cancer diagnosis using microarray datasets. / Gaafar, Mohammed A.; Yousri, Noha; Ismail, Mohamed A.

IEEE 12th International Conference on BioInformatics and BioEngineering, BIBE 2012. 2012. p. 368-373 6399652.

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

Gaafar, MA, Yousri, N & Ismail, MA 2012, A novel ensemble selection method for cancer diagnosis using microarray datasets. in IEEE 12th International Conference on BioInformatics and BioEngineering, BIBE 2012., 6399652, pp. 368-373, 12th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2012, Larnaca, Cyprus, 11/11/12. https://doi.org/10.1109/BIBE.2012.6399652
Gaafar MA, Yousri N, Ismail MA. A novel ensemble selection method for cancer diagnosis using microarray datasets. In IEEE 12th International Conference on BioInformatics and BioEngineering, BIBE 2012. 2012. p. 368-373. 6399652 https://doi.org/10.1109/BIBE.2012.6399652
Gaafar, Mohammed A. ; Yousri, Noha ; Ismail, Mohamed A. / A novel ensemble selection method for cancer diagnosis using microarray datasets. IEEE 12th International Conference on BioInformatics and BioEngineering, BIBE 2012. 2012. pp. 368-373
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