<aside> 💡
The Davies-Bouldin Index (DBI) is another method for validating the clustering configuration.
</aside>
It’s based on a ratio between the within-cluster scatter and the between-cluster separation.
A lower DBI value indicates a model with better separation between the clusters. The index is calculated as follows:
$$ DBI = \frac{1}{k} \sum_{i=1}^k \max_{j \neq i} \left(\frac{s_i + s_j}{d_{ij}}\right) $$
where $s_i$ is the average distance of all points in the cluster to their centroid, $d_{ij}$ is the distance between centroids of clusters i and j, and k is the number of clusters.
Next reading: