Explain the different linkage methods used in the Hierarchical Clustering Algorithm

Data Science, AI and ML
,
#1

The popular linkage methods used in Hierarchical Clustering are as follows:

Complete-linkage: In this method, the distance between two clusters is defined as the maximum distance between two data points from each cluster.

Single-linkage: In this method, the distance between two clusters is defined as the minimum distance between two data points in each cluster.

Average-linkage: In this method, the distance between two clusters is defined as the average distance between each data point in one cluster to every data point in the other cluster.

Centroid-linkage: In this method, we find the centroid of cluster 1 and the centroid of cluster 2 and then calculate the distance between the two before merging.