V-Measure (Rosenberg, 2007) Implementation in R. This almost exactly follows scikit-learn's implementation (http://scikit-learn.org/stable/modules/generated/sklearn.metrics.homogeneity_completeness_v_measure.html)

vmeasure.R

library(infotheo)

v.measure <- function(a, b) {
  mi <- mutinformation(a, b)
  entropy.a <- entropy(a)
  entropy.b <- entropy(b)
  if (entropy.a == 0.0) {
    homogeneity <- 1.0
  } else {
    homogeneity <- mi / entropy.a
  }
  if (entropy.b == 0.0) {
    completeness <- 1.0
  } else {
    completeness <- mi / entropy.b
  }
  if (homogeneity + completeness == 0.0) {
    v.measure.score <- 0.0
  } else {
    v.measure.score <- (2.0 * homogeneity * completeness
                        / (homogeneity + completeness))
  }
  # Can also return homogeneity and completeness if wanted
  v.measure.score
}