experiments/WCCI2022/evaluation.R

In noeliarico/mchclust:

library(fossil)

evaluate_results <- function(data, mchc) {
  if(class(mchc) == "hclust") {
    clusters <- cutree(mchc, length(unique(data$class)))

  } else {
    clusters <- get_clusters(mchc, length(unique(data$class)))
  }

  # cm <- table(clusters, data$class)
  #
  # cat(paste0("Correct: ", sum(diag(cm)), "/", sum(cm), " - ",  round(sum(diag(cm))*100/sum(cm), 2), "%"))
  #
  # res <- fpc::cluster.stats(dist(data[,1:2]),
  #                           as.numeric(data$class),
  #                           as.numeric(clusters))
  #
  # res <- tibble::tibble(
  #   total = length(data$class),
  #   correct  = sum(diag(cm)),
  #   entropy = res$entropy,
  #   dunn = res$dunn,
  #   rand = res$corrected.rand,
  #   vi = res$vi
  # )

  res <- tibble::tibble(
    ri = rand.index(classes, clusters),
  )

  return(res)

}