vmeasure: V-measure
In SBMSplitMerge: Inference for a Generalised SBM with a Split Merge Sampler

Description Usage Arguments Details Value See Also Examples

Calculate the V-measure of two clusterings

1	vmeasure(z, truez, beta = 1)

`z`	input vector
`truez`	reference vector
`beta`	parameter `beta=1` gives equal weight to homogeneity and completeness

An information based measure of similarity between two clusterings

v-measure of z against truez

Rosenberg, A., & Hirschberg, J. (2007, June). V-measure: A conditional entropy-based external cluster evaluation measure. In Proceedings of the 2007 joint conference on empirical methods in natural language processing and computational natural language learning (EMNLP-CoNLL) (pp. 410-420).

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vmeasure(c(1,1,2,2,3,3), c(2,2,1,1,3,3)) ## 1 - doesn't care for labels
vmeasure(c(1,1,2,2,3,3), c(1,1,2,2,2,2)) ## 0.7333
vmeasure(c(1,1,2,2,3,3), c(1,1,2,2,3,4)) ## 0.904