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ML | Types of links in clustering

The hierarchical clustering process involves either clustering subclusters (data points in the first iteration) into larger clusters in an upward fashion, or dividing a larger cluster into smaller subclusters from top to bottom. During both types of hierarchical clustering, it is necessary to calculate the distance between the two subclusters. Different types of links describe different approaches for measuring the distance between two subgroups of data points. Different types of links:

1. Single link: for two clusters R and S, a single link returns the minimum distance between two points i and j, so that i belongs to R and j belongs S.

2. Full link: for two clusters R and S, a single link returns the maximum distance between two points i and j so i belongs to R and j belongs to S.

3. Average link: for two clusters R and S, first for the distance between any data point i in R and any data point j in S, and then the arithmetic mean of these distances is calculated. Average binding returns this arithmetic mean.

where

— Number of data points in R

— Number of data points in S

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