| 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)