The Dunn Index

The Dunn Index is a metric used to evaluate the quality of clustering in data analysis. It measures how well data points are grouped into distinct clusters by comparing the distance between different clusters (inter-cluster separation) to the spread of points within each cluster (intra-cluster cohesion). A higher Dunn Index indicates that clusters are well-separated and compact, signifying good clustering, while a lower value suggests overlapping or poorly defined groups. Essentially, it helps determine how effectively the data has been partitioned into meaningful, distinct groups.