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Use of Factor Analyzer Normal Mixture Model with Mean Pattern Modeling on Clustering Genes
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 Title & Authors
Use of Factor Analyzer Normal Mixture Model with Mean Pattern Modeling on Clustering Genes
Kim Seung-Gu;
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Normal mixture model(NMM) frequently used to cluster genes on microarray gene expression data. In this paper some of component means of NMM are modelled by a linear regression model so that its design matrix presents the pattern between sample classes in microarray matrix. This modelling for the component means by given design matrices certainly has an advantage that we can lead the clusters that are previously designed. However, it suffers from 'overfitting' problem because in practice genes often are highly dimensional. This problem also arises when the NMM restricted by the linear model for component-means is fitted. To cope with this problem, in this paper, the use of the factor analyzer NMM restricted by linear model is proposed to cluster genes. Also several design matrices which are useful for clustering genes are provided.
Clustering genes;Design matrix;Factor analyzer normal mixture model;
 Cited by
이분산 상황 하에서 정규혼합모형 기반 군집분석의 변수선택,김승구;

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