An implementation of Multi-View Clustering (Bickel and Scheffer, 2004). Documents are generated by drawing word values from a categorical distribution for each word, given the cluster. This means words are not counted (multinomial, as in the paper), but words take on different values from a finite set of values (categorical). Thus, it implements Mixture of Categoricals EM (as opposed to Mixture of Multinomials developed in the paper), and Spherical k-Means. The latter represents documents as vectors in the categorical space.
|Depends:||R (≥ 2.14.1), rattle (≥ 2.6.18)|
|Maintainer:||Andreas Maunz <andreas at maunz.de>|
|License:||BSD_3_clause + file LICENSE|
|CRAN checks:||mvc results|
|Windows binaries:||r-devel: mvc_1.3.zip, r-release: mvc_1.3.zip, r-oldrel: mvc_1.3.zip|
|OS X Mavericks binaries:||r-release: mvc_1.3.tgz, r-oldrel: mvc_1.3.tgz|
|Old sources:||mvc archive|
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