High-Dimensional Bayesian Clustering with Variable Selection: The R Package bclus
The R package bclust is useful for clustering high-dimensional continuous data. The package uses a parametric spike-and-slab Bayesian model to downweight the effect of noise variables and to quantify the importance of each variable in agglomerative clustering. We take advantage of the existence of closed-form marginal distributions to estimate the model hyper-parameters using empirical Bayes, thereby yielding a fully automatic method. We discuss computational problems arising in implementation of the procedure and illustrate the usefulness of the package through examples.
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Keywords: agglomerative clustering ; Bayesian clustering ; Bayesian variable selection ; dendrogram ; hierarchical clustering ; R ; spike-and-slab model ; Geometric Representation ; Microarray Experiments ; Expression Data ; Mixture Model ; Regression
Record created on 2012-06-01, modified on 2016-08-09