High dimensional microarray data classification using correlation based feature selection

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

6 Citations (Scopus)

Abstract

Analyzing DNA microarray data pose a serious challenge because of their large number of features (genes) and relatively small number of samples. Extracting features, those have predictive capability for classifying these huge datasets
demands appropriate approaches like feature reduction and identifying optimal set of genes. In this paper along with conventional statistical methods like filtering the dataset to reduce the number of features, one additional approach of evaluating correlation between the classes for each feature is performed. Proposed approach yields higher classification accuracy for both Acute Lymphoblastic (ALL) and High Grade Glioma cancer dataset than using only traditional statistical filtering methods.
Original languageEnglish
Title of host publication2012 International Conference on Biomedical Engineering (ICoBE)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages319-321
Number of pages3
ISBN (Electronic)9781457719912
ISBN (Print)9781457719905
DOIs
Publication statusPublished - 27 Feb 2012
Externally publishedYes
Event2012 International Conference on Biomedical Engineering (ICoBE) - Penang, Malaysia
Duration: 27 Feb 201228 Feb 2012

Conference

Conference2012 International Conference on Biomedical Engineering (ICoBE)
CountryMalaysia
CityPenang
Period27/02/1228/02/12

Keywords

  • DNA microarray data
  • correlation
  • feature selection
  • classification

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  • Cite this

    Hassan, A., & Adnan, M. A. (2012). High dimensional microarray data classification using correlation based feature selection. In 2012 International Conference on Biomedical Engineering (ICoBE) (pp. 319-321). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICoBE.2012.6179029