R: Affinity Propagation

affin.prop {swfscMisc} | R Documentation

## Affinity Propagation

### Description

Runs the Affinity Propagation clustering algorithm of Frey and Dueck, 2007.

### Usage

    affin.prop(sim.mat, num.iter = 100, stable.iter = 10, shared.pref = "min",
      lambda = 0.5)

### Arguments

`sim.mat` | a similarity matrix between individuals to be clustered.
`num.iter` | maximum number of iterations to attempt.
`stable.iter` | number of sequential iterations for which consistent clustering is considered acceptable.
`shared.pref` | type of shared preference to use. Can be one of "min", "median", or a numeric value.
`lambda` | damping factor.

### Value

A matrix with one row per sample in 'sim.mat' and one column for each iteration. Values in columns indicate cluster assignment (arbitrary numbers) for each sample.

### Author(s)

Eric Archer eric.archer@noaa.gov

### References

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

### Examples

    data(iris)

    # Take 75 random iris rows for example
    iris <- iris[sample(1:nrow(iris), 75), ]
    iris <- droplevels(iris)

    iris.sim <- -dist(iris[, -5])

    iris.affin <- affin.prop(iris.sim, stable.iter = 5)
    table(iris$Species, iris.affin[, ncol(iris.affin)])

[Package swfscMisc version 1.2 Index]