Cluster validation based on nearest neighbours
Cluster validity index based on nearest neighbours as defined in Liu et al. (2013) with a correction explained in Halkidi et al. (2015).
cvnn(d=NULL,clusterings,k=5)
d |
dissimilarity matrix or |
clusterings |
list of vectors of integers with length |
k |
integer. Number of nearest neighbours. |
List with components (see Liu et al. (2013), Halkidi et al. (2015) for details)
cvnnindex |
vector of index values for the various clusterings, see Liu et al. (2013), the lower the better. |
sep |
vector of separation values. |
comp |
vector of compactness values. |
Halkidi, M., Vazirgiannis, M. and Hennig, C. (2015) Method-independent
indices for cluster validation. In C. Hennig, M. Meila, F. Murtagh,
R. Rocci (eds.) Handbook of Cluster Analysis, CRC
Press/Taylor & Francis, Boca Raton.
Liu, Y, Li, Z., Xiong, H., Gao, X., Wu, J. and Wu, S. (2013) Understanding and enhancement of internal clustering validation measures. IEEE Transactions on Cybernetics 43, 982-994.
options(digits=3) iriss <- as.matrix(iris[c(1:10,51:55,101:105),-5]) irisc <- as.numeric(iris[c(1:10,51:55,101:105),5]) print(cvnn(dist(iriss),list(irisc,rep(1:4,5))))
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