A conditional entropy-based external cluster evaluation measure.

vmeasure(x, y, z = NULL, B = 1)

Arguments

x

A numeric vector, representing a categorical values.

y

A numeric vector, representing a categorical values.

z

A numeric matrix. A contingency table of the counts at each combination of categorical levels. By default this argument is set to NULL, and the value of z is calculated based on x and y.

B

A numeric value. If B > 1 then completeness is weighted more strongly than homogeneity, and if B < 1 then homogeneity is weighted more strongly than completeness. By default this value is 1.

Value

A list with three elements:

  • "v_measure"

  • "homogeneity"

  • "completeness"

References

Rosenberg, Andrew, and Julia Hirschberg. "V-measure: A conditional entropy-based external cluster evaluation measure." Proceedings of the 2007 joint conference on empirical methods in natural language processing and computational natural language learning (EMNLP-CoNLL). 2007.

Examples

x = c(1, 1, 1, 2, 2, 3, 3, 3, 1, 1, 2, 2, 2, 3, 3) y = c(rep(1, 5), rep(2, 5), rep(3, 5)) vmeasure(x, y)
#> Results: #> #> V-measure: 0.39 #> Homogeneity: 0.39 #> Completeness: 0.39