%0 Journal Article
	%A Parvaneh Shabanzadeh and  Malik Hj Abu Hassan and  Leong Wah June and  Maryam Mohagheghtabar
	%D 2010
	%J International Journal of Mathematical and Computational Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 38, 2010
	%T Using Pattern Search Methods for Minimizing Clustering Problems
	%U https://publications.waset.org/pdf/1125
	%V 38
	%X 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.
	%P 325 - 329