apcluster (version 1.0.2)

preferenceRange: Determine Meaningful Ranges for Input Preferences

Description

Determines meaningful ranges for affinity propagation input preference

Usage

preferenceRange(s, exact=FALSE)

Arguments

s

an $l\times l$ similarity matrix

exact

flag indicating whether exact ranges should be computed, which is relatively slow; if bounds are sufficient, supply FALSE (default)

Value

• Returns a vector with two entries, the first of which is the minimal input preference (which would lead to 1 or 2 clusters) and the second of which is the maximal input prefence (which would lead to as many clusters as data samples).

Details

Affinity Propagation clustering relies on an appropriate choice of input preferences. This function helps in finding a good choice by determining meaningful lower and upper bounds.

References

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

Frey, B. J. and Dueck, D. (2007) Clustering by passing messages between data points. Science 315, 972-976.

See Also

apcluster

Examples

## create two Gaussian clouds
cl1 <- cbind(rnorm(100,0.2,0.05),rnorm(100,0.8,0.06))
cl2 <- cbind(rnorm(50,0.7,0.08),rnorm(50,0.3,0.05))
x <- rbind(cl1,cl2)

## create similarity matrix
sim <- negDistMat(x, r=2)

## determine bounds
preferenceRange(sim)

## determine exact range
preferenceRange(sim, exact=TRUE)