Pairwise Variable Selection for High-Dimensional Model-Based Clustering
نویسندگان
چکیده
منابع مشابه
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 separable by this variable and removed if it cannot separate any of the clusters. In many applicat...
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ژورنال
عنوان ژورنال: Biometrics
سال: 2009
ISSN: 0006-341X
DOI: 10.1111/j.1541-0420.2009.01341.x