Least-Squares Bilinear Clustering for Three-Way Data

Functions for performing least-squares bilinear clustering of three-way data. The method uses the bilinear decomposition (or bi-additive model) to model two-way matrix slices while clustering over the third way. Up to four different types of clusters are included, one for each term of the bilinear decomposition. In this way, matrices are clustered simultaneously on (a subset of) their overall means, row margins, column margins and row-column interactions. The orthogonality of the bilinear model results in separability of the joint clustering problem into four separate ones. Three of these sub-problems are specific k-means problems, while a special algorithm is implemented for the interactions. Plotting methods are provided, including biplots for the low-rank approximations of the interactions.


Reference manual

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1.1 by Pieter Schoonees, a year ago

Browse source code at https://github.com/cran/lsbclust

Authors: Pieter Schoonees [aut, cre] , Patrick Groenen [ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports plyr, clue, grid, gridExtra, reshape2, Rcpp, mvtnorm, graphics, methods, doParallel, foreach, parallel

Depends on stats, ggplot2

Linking to Rcpp

Imported by ccrs.

See at CRAN