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Pairwise Variable Selection for High-dimensional Model-based Clustering

Variable selection for clustering is an important and challenging problem in high-dimensional data analysis. Existing variable selection methods for model-based clustering select informative variables in a “one-in-all-out” manner; that is, a variable is selected if at least one pair of clusters is s...

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Hlavní autoři: Guo, Jian, Levina, Elizaveta, Michailidis, George, Zhu, Ji
Médium: Artigo
Jazyk:Inglês
Vydáno: 2010
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC2888949/
https://ncbi.nlm.nih.gov/pubmed/19912170
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/j.1541-0420.2009.01341.x
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