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Normal Mixture Model with General Linear Regressive Restriction: Applied to Microarray Gene Clustering
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 Title & Authors
Normal Mixture Model with General Linear Regressive Restriction: Applied to Microarray Gene Clustering
Kim, Seung-Gu;
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In this paper, the normal mixture model subjected to general linear restriction for component-means based on linear regression is proposed, and its fitting method by EM algorithm and Lagrange multiplier is provided. This model is applied to gene clustering of microarray expression data, which demonstrates it has very good performances for real data set. This model also allows to obtain the clusters that an analyst wants to find out in the fashion that the hypothesis for component-means is represented by the design matrices and the linear restriction matrices.
Normal mixture model;general linear restriction;EM algorithm;microarray;gene clustering;
 Cited by
합성된 평균과 분산을 가진 군집 식별,김승구;

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