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lsbclust  

Least-Squares Bilinear Clustering for Three-Way Data
View on CRAN: Click here


Download and install lsbclust package within the R console
Install from CRAN:
install.packages("lsbclust")

Install from Github:
library("remotes")
install_github("cran/lsbclust")

Install by package version:
library("remotes")
install_version("lsbclust", "1.1")



Attach the package and use:
library("lsbclust")
Maintained by
Pieter Schoonees
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-02-11
Latest Update:
Description:
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.
How to cite:
Pieter Schoonees (2015). lsbclust: Least-Squares Bilinear Clustering for Three-Way Data. R package version 1.1, https://cran.r-project.org/web/packages/lsbclust. Accessed 06 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:54), 1.0.1 (2015-02-16 14:08), 1.0.2 (2015-03-12 01:11), 1.0.3 (2015-08-15 00:59), 1.0.4 (2016-01-05 14:18), 1.0.5 (2018-04-19 22:26), 1.0 (2015-02-11 01:32), 1.1 (2019-04-15 11:32)
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Complete documentation for lsbclust
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