A derivative-free optimization method for solving classification problem

Problem statement: The aim of data classification is to establish rules for the classification of some observations assuming that we have a database, which includes of at least two classes. There is a training set for each class. Those problems occur in a wide range of human activity. One of the mos...

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Main Authors: Shabanzadeh, Parvaneh, Abu Hassan, Malik, Leong, Wah June
格式: Article
语言:English
出版: Science Publications 2010
在线阅读:http://psasir.upm.edu.my/id/eprint/12683/1/12683.pdf
http://psasir.upm.edu.my/id/eprint/12683/
http://thescipub.com/abstract/10.3844/jcssp.2010.369.373
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spelling my.upm.eprints.126832019-10-09T08:19:55Z http://psasir.upm.edu.my/id/eprint/12683/ A derivative-free optimization method for solving classification problem Shabanzadeh, Parvaneh Abu Hassan, Malik Leong, Wah June Problem statement: The aim of data classification is to establish rules for the classification of some observations assuming that we have a database, which includes of at least two classes. There is a training set for each class. Those problems occur in a wide range of human activity. One of the most promising ways to data classification is based on methods of mathematical optimization. Approach: The problem of data classification was studied as a problem of global, nonsmooth and nonconvex optimization; this approach consists of describing clusters for the given training sets. The data vectors are assigned to the closest cluster and correspondingly to the set, which contains this cluster and an algorithm based on a derivative-free method is applied to the solution of this problem. Results: Proposed method had been tested on real-world datasets. Results of numerical experiments had been presented which demonstrate the effectiveness of the proposed algorithm. Conclusion: In this study we had studied a derivative-free optimization approach to the classification. For optimization generalized pattern search method has been applied. The results of numerical experiments allowed us to say the proposed algorithms are effective for solving classification problems at least for databases considered in this study. Science Publications 2010-03-31 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/12683/1/12683.pdf Shabanzadeh, Parvaneh and Abu Hassan, Malik and Leong, Wah June (2010) A derivative-free optimization method for solving classification problem. Journal of Computer Science, 6 (3). pp. 369-373. ISSN 1549-3636; ESSN: 1552-6607 http://thescipub.com/abstract/10.3844/jcssp.2010.369.373 10.3844/jcssp.2010.369.373
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Problem statement: The aim of data classification is to establish rules for the classification of some observations assuming that we have a database, which includes of at least two classes. There is a training set for each class. Those problems occur in a wide range of human activity. One of the most promising ways to data classification is based on methods of mathematical optimization. Approach: The problem of data classification was studied as a problem of global, nonsmooth and nonconvex optimization; this approach consists of describing clusters for the given training sets. The data vectors are assigned to the closest cluster and correspondingly to the set, which contains this cluster and an algorithm based on a derivative-free method is applied to the solution of this problem. Results: Proposed method had been tested on real-world datasets. Results of numerical experiments had been presented which demonstrate the effectiveness of the proposed algorithm. Conclusion: In this study we had studied a derivative-free optimization approach to the classification. For optimization generalized pattern search method has been applied. The results of numerical experiments allowed us to say the proposed algorithms are effective for solving classification problems at least for databases considered in this study.
format Article
author Shabanzadeh, Parvaneh
Abu Hassan, Malik
Leong, Wah June
spellingShingle Shabanzadeh, Parvaneh
Abu Hassan, Malik
Leong, Wah June
A derivative-free optimization method for solving classification problem
author_facet Shabanzadeh, Parvaneh
Abu Hassan, Malik
Leong, Wah June
author_sort Shabanzadeh, Parvaneh
title A derivative-free optimization method for solving classification problem
title_short A derivative-free optimization method for solving classification problem
title_full A derivative-free optimization method for solving classification problem
title_fullStr A derivative-free optimization method for solving classification problem
title_full_unstemmed A derivative-free optimization method for solving classification problem
title_sort derivative-free optimization method for solving classification problem
publisher Science Publications
publishDate 2010
url http://psasir.upm.edu.my/id/eprint/12683/1/12683.pdf
http://psasir.upm.edu.my/id/eprint/12683/
http://thescipub.com/abstract/10.3844/jcssp.2010.369.373
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