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Penalized model-based clustering with unconstrained covariance matrices

Clustering is one of the most useful tools for high-dimensional analysis, e.g., for microarray data. It becomes challenging in presence of a large number of noise variables, which may mask underlying clustering structures. Therefore, noise removal through variable selection is necessary. One effecti...

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Detaylı Bibliyografya
Asıl Yazarlar: Zhou, Hui, Pan, Wei, Shen, Xiaotong
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: 2009
Konular:
Online Erişim:https://ncbi.nlm.nih.gov/pmc/articles/PMC2867492/
https://ncbi.nlm.nih.gov/pubmed/20463857
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1214/09-EJS487
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