# Clustering evaluation metrics with subquadratic time complexity

It exists many evaluation metrics but often they are quadratic or more on number of data points preventing any application on massive data sets as RAND or Silhouette indexes.

For the moment i used :

## Internal metrics

• Davies Bouldin, which is in $O(n.c^2)$ with $c$ the number of clusters

I implemented both under Spark framework in Scala here for those who are interested but i would be happy to know if others exists, especially concerning internal metrics because even if Davies Bouldin could be a good evaluation metric, it is in my opinion, only with elliptic clusters.