Using Pattern Search Methods for Minimizing Clustering Problems

Shabanzadeh, Parvaneh and Abu Hassan, Malik and Leong, Wah June and Mohagheghtabar, Maryam (2010) Using Pattern Search Methods for Minimizing Clustering Problems. World Academy of Science, Engineering and Technology, 62 (February). pp. 158-162. ISSN 1307-6892

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Abstract

Clustering is one of an interesting data mining topics that can be applied in many fields. Recently, the problem of cluster analysis is formulated as a problem of nonsmooth, nonconvex optimization,and an algorithm for solving the cluster analysis problem based on nonsmooth optimization techniques is developed. This optimization problem has a number of characteristics that make it challenging: it has many local minimum, the optimization variables can be either continuous or categorical, and there are no exact analytical derivatives. In this study we show how to apply a particular class of optimization methods known as pattern search methods to address these challenges. These methods do not explicitly use derivatives, an important feature that has not been addressed in previous studies. Results of numerical experiments are presented which demonstrate the effectiveness of the proposed method.

Item Type:Article
Keyword:Clustering functions, Non-smooth Optimization, Nonconvex Optimization, Pattern Search Method
Subject:Cluster analysis
Subject:Mathematical optimization
Faculty or Institute:Faculty of Science
Publisher:World Academy of Science, ENG and Technology (WASET)
ID Code:17551
Deposited By: Najwani Amir Sariffudin
Deposited On:29 Mar 2012 09:06
Last Modified:29 Mar 2012 09:06

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