Functions for performing least-squares bilinear clustering of three-way data. The method uses the bilinear decomposition (or biadditive 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 subproblems 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.
|Author||Pieter Schoonees [aut, cre], Patrick Groenen [ctb]|
|Date of publication||2016-01-05 14:18:01|
|Maintainer||Pieter Schoonees <firstname.lastname@example.org>|
|License||GPL (>= 2)|
bicomp: Bilinear Decomposition of a Matrix
ClustMeans: C++ Function for Cluster Means
cmat: Centring Matrix
dcars: Dutch Cars Data
genproc: Generalized Procrustes Rotation
indarr: Create Array of Indicator Matrices
int.lsbclust: Interaction Clustering in Least Squares Bilinear Clustering
KMeansW: C++ Function for Weighted K-Means
LossMat: C++ Function for Interaction Loss Function
lov: List-of-values Data Set
lsbclust: Least-squares Bilinear Clustering of Three-way Data
lsbclust-package: Least Squares Latent Class Matrix Factorization
lsbclusttoclue: S3 Methods for Integration into 'clue' Framework
orc.lsbclust: K-means on the Overall Mean, Row Margins or Column Margins
plot.bicomp: Plot a 'bicomp' Object
plot.col.kmeans: Plot method for class 'col.kmeans'
plot.int.lsbclust: Plot Method for Class 'int.lsbclust'
plot.lsbclust: Plot method for class 'lsbclust'
plot.ovl.kmeans: Plot method for class 'ovl.kmeans'
plot.row.kmeans: Plot method for class 'row.kmeans'
plot.step.lsbclust: Plot method for class 'step.lsbclust'
print.lsbclust: Print method for object of class 'lsbclust'
sim.lsbclust: Simulate from an LSBLCUST model
step.lsbclust: Model Search for lsbclust
summary.int.lsbclust: Summary Method for Class "int.lsbclust"
summary.lsbclust: Summary Method for Class "lsbclust"
supermarkets: Dutch Supermarkets Data Set
T3Clusf: T3Clusf: Tucker3 Fuzzy Cluster Analysis