Vmeasure¶
The VMeasure is defined as the harmonic mean of homogeneity and completeness of the clustering. Both these measures can be expressed in terms of the mutual information and entropy measures of the information theory.
Homogeneity is maximized when each cluster contains elements of as few different classes as possible. Completeness aims to put all elements of each class in single clusters.
References:
Andrew Rosenberg and Julia Hirschberg, 2007. “VMeasure: A conditional entropybased external cluster evaluation measure”
The metric is implemented by the vmeasure
function:

vmeasure
(assign1, assign2; β = 1.0)¶ Compute Vmeasure value between two clustering assignments.
Parameters:  assign1 – the vector of assignments for the first clustering.
 assign2 – the vector of assignments for the second clustering.
 β – the weight of harmonic mean of homogeneity and completeness.
Returns: a Vmeasure value.

vmeasure
(R, assign) This method takes
R
, an instance ofClusteringResult
, and the corresponding assignment vectorassign
as input, and computes Vmeasure value (see above).

vmeasure
(R1, R2) This method takes
R1
andR2
(both are instances ofClusteringResult
) and computes Vmeasure value (see above).It is equivalent tovmeasure(assignments(R1), assignments(R1))
.