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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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| Hauptverfasser: | , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2010
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| Schlagworte: | |
| Online Zugang: | 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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