Open Access
2014 A New Method for Solving Supervised Data Classification Problems
Parvaneh Shabanzadeh, Rubiyah Yusof
Abstr. Appl. Anal. 2014: 1-9 (2014). DOI: 10.1155/2014/318478


Supervised data classification is one of the techniques used to extract nontrivial information from data. Classification is a widely used technique in various fields, including data mining, industry, medicine, science, and law. This paper considers a new algorithm for supervised data classification problems associated with the cluster analysis. The mathematical formulations for this algorithm are based on nonsmooth, nonconvex optimization. A new algorithm for solving this optimization problem is utilized. The new algorithm uses a derivative-free technique, with robustness and efficiency. To improve classification performance and efficiency in generating classification model, a new feature selection algorithm based on techniques of convex programming is suggested. Proposed methods are tested on real-world datasets. Results of numerical experiments have been presented which demonstrate the effectiveness of the proposed algorithms.


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Parvaneh Shabanzadeh. Rubiyah Yusof. "A New Method for Solving Supervised Data Classification Problems." Abstr. Appl. Anal. 2014 1 - 9, 2014.


Published: 2014
First available in Project Euclid: 27 February 2015

zbMATH: 1343.62038
MathSciNet: MR3285157
Digital Object Identifier: 10.1155/2014/318478

Rights: Copyright © 2014 Hindawi

Vol.2014 • 2014
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