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.
copheneticCorrelation(kernelMatrix)
| kernelMatrix | kernel matrix. |
|---|
This functions returns the cophenetic correlation coefficient of the kernel matrix provided as input.
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.
# 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)#> 0.9979256