separation: Average Separation of a clustering.
In laderast/Consense: Consense: a package for evaluating multiple clusterings

Description Usage Arguments Value Author(s) References Examples

Given cluster output from a suitable clustering function, calculate the separation (from Shamir, et al.) of the clusterings. Homogeneity can be thought of as a measure of the average between-cluster distance within a clustering.

1	separation(clustering, centers)

`clustering`	Cluster output from a clustering function. the output should be in matrix format with the cluster assignments being the first column in that matrix, with the actual data in remaining columns.
`centers`	Cluster centers from `clusterCenters`.

separation

An unbounded, non-negative scalar that represents the separation of the clustering.

Ted Laderas (laderast@ohsu.edu)

Shamir, et al. Algorithmic Approaches to Clustering Gene Expression Data. in Current Topics in Computational Molecular Biology. MIT Press: Boston.

##=don't run
    ##calculate separation for Cho et al's clusters
    data(chocellcycle)
    data(choclusters)
    cho <- cbind(as.numeric(choclusters), chocellcycle)
    cent <- clusterCenters(as.data.frame(cho))
    separation(cho, cent)