Computes the Davis-Bouldin-Index for cluster validation purposes.
Usage
DBIndex(data, labels)
Arguments
data
N x D matrix (N samples, D features)
labels
a vector of class labels
Value
'DBIndex' returns the Davis-Bouldin cluster index, a numeric value.
Details
To compute a clusters' compactness, this version uses the Euclidean distance to
determine the mean distances between the samples and the cluster centers.
Furthermore, the distance of two clusters is given by the distance of their centers.
## DB-Index of a 50 dimensional dataset with 20 samples separated into two classesd = generateData(samples=20, genes=50, diffgenes=10, blocksize=5)
DBIndex (data=d[[1]], labels=d[[2]])