A New Method for Solving Supervised Data Classification Problems
Joint Authors
Shabanzadeh, Parvaneh
Yusof, Rubiyah
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-11-27
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Shabanzadeh, Parvaneh& Yusof, Rubiyah. 2014. A New Method for Solving Supervised Data Classification Problems. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1033685
Modern Language Association (MLA)
Shabanzadeh, Parvaneh& Yusof, Rubiyah. A New Method for Solving Supervised Data Classification Problems. Abstract and Applied Analysis No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1033685
American Medical Association (AMA)
Shabanzadeh, Parvaneh& Yusof, Rubiyah. A New Method for Solving Supervised Data Classification Problems. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1033685
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1033685