How can we measure the goodness of the clusters in the Hierarchical Clustering Algorithm?

Data Science, AI and ML
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#1

There are many measures to find the goodness of clusters but the most popular one is the Dunn’s Index.

Dunn’s index is defined as the ratio of the minimum inter-cluster distances to the maximum intra-cluster diameter and the diameter of a cluster is calculated as the distance between its two furthermost points i.e, maximum distance from each other.

Conclusion:

  • In order to have well separated and compact clusters, we should aim for a higher value of Dunn’s index.

Assessment Metrics for Clustering Algorithms

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