NMF (version 0.5.06)

NMFOffset-class: Nonnegative Matrix Factorization with Offset

Description

Class that implements the Nonnegative Matrix Factorization with Offset model, required by the NMF with Offset algorithm. The NMF with Offset algorithm is defined by Badea (2008) as a modification of Lee & Seung's euclidean based NMF algorithm (see section Details and references below). It aims at obtaining 'cleaner' factor matrices, by the introduction of an offset matrix, explicitly modelling a feature specific baseline -- constant across samples.

Objects from the Class

Object of class NMFOffset can be created using the standard way with operator new However, as for all the classes that extend class NMFstd, objects of class NMFOffset should be created using factory method nmfModel : new('NMFOffset') nmfModel(model='NMFOffset') nmfModel(model='NMFOffset', W=w, offset=rep(1, nrow(w))) See nmfModel for more details on how to use the factory method.

Extends

Class "NMF", directly.

References

Badea (2008). Extracting Gene Expression Profiles Common To Colon And Pancreatic Adenocaricinoma Using Simultaneous Nonnegative Matrix Factorization. In Pacific Symposium on Biocomputing , 13, 279-290

See Also

NMF, nmf-methods

Examples

# create a completely empty NMF object
new('NMFOffset')

# create a NMF object based on random (compatible) matrices
n <- 50; r <- 3; p <- 20
w <- matrix(runif(n*r), n, r) 
h <- matrix(runif(r*p), r, p)
nmfModel(model='NMFOffset', W=w, H=h, offset=rep(0.5, nrow(w)))

# apply Nonsmooth NMF algorithm to a random target matrix
V <- matrix(runif(n*p), n, p)
nmf(V, r, 'offset')