Davies-Bouldin Index

The Davies-Bouldin Index is a metric used to evaluate clustering algorithms. It measures the average similarity ratio of each cluster with its most similar cluster, where lower values indicate better clustering performance. The index is calculated by assessing the distance between clusters and the dispersion within each cluster. It is commonly used in data science and machine learning to compare the effectiveness of different clustering techniques and to help determine the optimal number of clusters in a dataset.