Davies-Bouldin index

The Davies-Bouldin index is a measurement used to evaluate how well a clustering algorithm has grouped data points. It compares clusters based on how close the points are within each cluster (compactness) and how far apart the clusters are from each other (separation). A lower index value indicates that clusters are tightly grouped internally and well separated from one another, implying better clustering quality. Conversely, a higher value suggests overlapping or loosely grouped clusters. This helps in choosing the best number of clusters or assessing the effectiveness of a clustering method.