copheneticCorrelation {klic} | R Documentation |
Cophenetic correlation coefficient
Description
Compute the cophenetic correlation coefficient of a kernel matrix, which is a measure of how faithfully hierarchical clustering would preserve the pairwise distances between the original data points.
Usage
copheneticCorrelation(kernelMatrix)
Arguments
kernelMatrix |
kernel matrix. |
Value
This functions returns the cophenetic correlation coefficient of the kernel matrix provided as input.
Author(s)
Alessandra Cabassi alessandra.cabassi@mrc-bsu.cam.ac.uk
References
Cabassi, A. and Kirk, P. D. W. (2019). Multiple kernel learning for integrative consensus clustering of genomic datasets. arXiv preprint. arXiv:1904.07701.
Sokal, R.R. and Rohlf, F.J., 1962. The comparison of dendrograms by objective methods. Taxon, 11(2), pp.33-40.
Examples
# Load kernel matrix
consensus_matrix <- as.matrix(read.csv(system.file('extdata',
'consensus_matrix1.csv', package = 'klic'), row.names = 1))
# Compute cophenetic correlation
coph_corr_coeff <- copheneticCorrelation(consensus_matrix)
cat(coph_corr_coeff)
[Package klic version 1.0.4 Index]