cutree-methods {apcluster} | R Documentation |

## Cut Out Clustering Level from Cluster Hierarchy

### Description

Cut out a clustering level from a cluster hierarchy

### Usage

```
## S4 method for signature 'AggExResult'
cutree(tree, k, h)
## S4 method for signature 'APResult'
cutree(tree, k, h)
```

### Arguments

`tree` |
an object of class |

`k` |
the level (i.e. the number of clusters) to be selected |

`h` |
alternatively, the level can be selected by specifying a cut-off for the merging objective |

### Details

The function `cutree`

extracts a clustering level from a
cluster hierarchy stored in an `AggExResult`

object. Which level is selected can be determined by one of the
two arguments `k`

and `h`

(see above). If both `k`

and
`h`

are specified, `k`

overrides `h`

. This is
done largely analogous to the standard function
`cutree`

. The differences are (1) that
only one level can be extracted at a time and (2) that an
`ExClust`

is returned instead of an index list.

The function `cutree`

may further be used to convert an
`APResult`

object into an
`ExClust`

object. In this case, the arguments
`k`

and `h`

are ignored.

### Value

returns an object of class `ExClust`

### Author(s)

Ulrich Bodenhofer & Andreas Kothmeier apcluster@bioinf.jku.at

### References

http://www.bioinf.jku.at/software/apcluster/

Bodenhofer, U., Kothmeier, A., and Hochreiter, S. (2011)
APCluster: an R package for affinity propagation clustering.
*Bioinformatics* **27**, 2463-2464.
DOI: doi:10.1093/bioinformatics/btr406.

### See Also

### Examples

```
## create two simple clusters
x <- c(1, 2, 3, 7, 8, 9)
names(x) <- c("a", "b", "c", "d", "e", "f")
## compute similarity matrix (negative squared distance)
sim <- negDistMat(x, r=2)
## run affinity propagation
aggres <- aggExCluster(sim)
## show details of clustering results
show(aggres)
## retrieve clustering with 2 clusters
cutree(aggres, 2)
## retrieve clustering with cut-off h=-1
cutree(aggres, h=-1)
```

*apcluster*version 1.4.11 Index]