DISTINGUISHABILITY BASED WEIGHTED FEATURE SELECTION USING COLUMN WISE K NEIGHBORHOOD FOR THE CLASSIFICATION OF GENE MICROARRAY DATASET
- 1 Department of Computer Science and Applications, Periyar Maniammai University, Vallam-613 403, Thanjavur, Tamilnadu, India
- 2 Department of Computer Science, Sri Ramakrishna Engineering College, Coimbatore, Tamilnadu, India
Abstract
In data mining, much research is being carried out to discover the previously unknown, valid, novel, useful and understandable patterns in large databases. The patterns must be actionable so that they might be used for decision making to a variety of applications in healthcare. In this study, feature subset selection is an important area, where many approaches have been proposed. Hence, the authors chosen three existing feature selection algorithms analyzed their performance using the publicly available standard colon tumor dataset. The performance of the existing three methods evaluated and compared each method with DWFS-CKN under study.
DOI: https://doi.org/10.3844/ajassp.2014.1.7
Copyright: © 2014 Jeyachidra and Punithavalli. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Feature Selection
- Microarray Data
- Classification
- C4.5
- Bayes