# ensemble: Ensemble Methods for Bicluster Algorithms In biclust: BiCluster Algorithms

## Description

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

## Usage

 ```1 2``` ```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`
 ```1 2 3 4 5 6 7 8 9``` ```## 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) ```