R: Ensemble Methods for Bicluster Algorithms

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

### See Also

`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 2.0.2 Index]