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)
```

*biclust*version 2.0.3.1 Index]