How to determine agreement between clustering methods? Let's say you want to compare the outcome of KMeans and KMedoids. How to determine if cluster 1 from KMeans can be compared with cluster 1 with KMedoids. Or, in other words, let's say KMeans labels the clusters as {0, 1, 2, 3} and KMedoids as {a, b, c, d}: how does one make the correct comparisons? In high dimensions, one cannot visually address which clusters overlap.
Kind regards,
Sean

A solution can be found in the following explanation:

Does one know whether a Python implementation of above recursion exists?
It would look something in line with:
grouped_together = pd.DataFrame()

for (i in 1:N){
  for (j in (i+1):(N-1)){
    for (k in 1:2){
      grouped_together[i,j,k]=A[i,k]==A[j,k]
    }
  }
}

