lsbclust - 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.
