ensemble {biclust} R Documentation

## Ensemble Methods for Bicluster Algorithms

### Description

Calculates an ensemble of biclusters from different parameter setting of possible different bicluster algorithms.

### Usage

ensemble(x, confs, rep = 1, maxNum = 5, similar = jaccard2, thr = 0.8, simthr =0.7,
subs = c(1, 1), bootstrap = FALSE, support = 0, combine=firstcome, ...)


### Arguments

 x Data Matrix confs Matrix containing parameter sets rep Number of repetitions for each parameter set maxNum Maximum number of biclusters taken from each run similar Function to produce a similarity matrix of bicluster thr Threshold for similarity simthr Proportion of row column combinations in bicluster subs Vector of proportion of rows and columns for subsampling. Default c(1,1) means no subsampling. bootstrap Should bootstrap sampling be used (logical: replace=bootstrap). support Which proportion of the runs must contain the bicluster to have enough support to report it (between 0 and 1). combine Function to combine the single bicluster only firstcome and hcl for hierarchical clustering are possible at the moment. ... Arguments past to the combine function.

### Details

Two different kinds (or both combined) of ensembling is possible. Ensemble of repeated runs or ensemble of runs on subsamples.

### Value

Return an object of class Biclust

### Author(s)

Sebastian Kaiser sebastian.kaiser@stat.uni-muenchen.de

Biclust-class, plaid.grid, bimax.grid

### Examples


## Not run:
data(BicatYeast)
ensemble.plaid <- ensemble(BicatYeast,plaid.grid()[1:5],rep=1,maxNum=2, thr=0.5, subs = c(1,1))
ensemble.plaid
x <- binarize(BicatYeast)
ensemble.bimax <- ensemble(x,bimax.grid(),rep=10,maxNum=2,thr=0.5, subs = c(0.8,0.8))
ensemble.bimax

## End(Not run)


[Package biclust version 2.0.3.1 Index]