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Prerequisites: Hierarchical Clustering The process of Hierarchical Clustering
involves either clustering sub-clusters(data points in the first iteration) into
larger clusters in a bottom-up manner or dividing a larger cluster into smaller
sub-clusters in a top-down manner. During both the types of hierarchical
clustering, the distance between two sub-clusters needs to be computed. The
different types of linkages describe the different approaches to measure the
distance between two sub-clusters of data points. The different types of
linkages are:- 1. Single Linkage: For two clusters R and S, the single linkage
returns the minimum distance between two points i and j such that i belongs to
R and j belongs to S.
2. Complete Linkage: For two clusters R and S, the complete linkage returns the
maximum distance between two points i and j such that i belongs to R and j
belongs to S.
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3. Average Linkage: 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 are calculated. Average Linkage returns this value of the arithmetic
mean.
where
– Number of data-points in R
– Number of data-points in S
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Last Updated : 25 Oct, 2021
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