%0 Journal Article
	%A Nazif Çalış and  Murat Erişoğlu and  Hamza Erol and  Tayfun Servi
	%D 2011
	%J International Journal of Mathematical and Computational Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 55, 2011
	%T Self Organizing Mixture Network in Mixture Discriminant Analysis: An Experimental Study
	%U https://publications.waset.org/pdf/5583
	%V 55
	%X In the recent works related with mixture discriminant
analysis (MDA), expectation and maximization (EM) algorithm is
used to estimate parameters of Gaussian mixtures. But, initial values
of EM algorithm affect the final parameters- estimates. Also, when
EM algorithm is applied two times, for the same data set, it can be
give different results for the estimate of parameters and this affect the
classification accuracy of MDA. Forthcoming this problem, we use
Self Organizing Mixture Network (SOMN) algorithm to estimate
parameters of Gaussians mixtures in MDA that SOMN is more robust
when random the initial values of the parameters are used [5]. We
show effectiveness of this method on popular simulated waveform
datasets and real glass data set.
	%P 1015 - 1018