文章基本信息

标题：Improved LDA by using Distributing Distances and Boundary Patterns
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作者：Ali Yaghoubi ; Hamid Reza Ghaffari
期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2015
卷号：4
期号：6
页码：143-147
出版社：International Journal of Soft Computing & Engineering
摘要：One of the statistical methods of class discriminant is linear discriminant analysis. This method, by using statistical parameters, obtain a space which by using available discriminating information among class means does classification act . By using distributing Distances, extended analysis linear discriminant to its heteroscedastic state. At this state ,to make classes more separating of available separating information among covariance matrix classes including classes mean is using. In this article ,because of using new scattering matrices which are defined based on boundary and non- boundary patterns, classes overlapping in Spaces which obtains has been reduced . On the other hand ,using new scattering matrices brings about increasing classification rate so, the done experiments confirm improvement of classification rate
关键词：boundary linear discriminant analysis; Boundary and;non-boundary patterns; CHernoff criteria; linear discriminant;analysis.