Based on a posterior similarity matrix of a sample of clusterings medv obtains a clustering by using 1-psm as distance
matrix for hierarchical clustering with complete linkage. The dendrogram is cut at a value h close to 1.
Usage
medv(psm, h=0.99)
Arguments
psm
a posterior similarity matrix, usually obtained from a call to comp.psm.
Medvedovic, M. Yeung, K. and Bumgarner, R. (2004) Bayesian mixture model based clustering
of replicated microarray data, Bioinformatics, 20, 1222-1232.
See Also
comp.psm for computing posterior similarity matrix, maxpear, minbinder, relabel
for other possibilities for processing a sample of clusterings.
Examples
data(cls.draw1.5)
# sample of 500 clusterings from a Bayesian cluster model
tru.class <- rep(1:8,each=50)
# the true grouping of the observations
psm1.5 <- comp.psm(cls.draw1.5)
medv1.5 <- medv(psm1.5)
table(medv1.5, tru.class)