Single Linkage Hierarchical Clustering | Step-by-Step Solved Example | Agglomerative Clustering

Single Linkage Hierarchical Clustering | Agglomerative Method | Solved Numerical Example | Machine Learning by Vidya Mahesh Huddar

Single inkage CLustering: https://youtu.be/-oPyDp1IpV4
Complete inkage CLustering: https://youtu.be/ADRRbUSoIAc

In this video, we explain Single Linkage Hierarchical Clustering using the Agglomerative Method with a complete solved numerical example.

Step-by-step, we:

• Start with initial clusters (each data point as a separate cluster)
• Calculate Euclidean distances
• Find the minimum distance between clusters
• Merge clusters using the Single Linkage (minimum distance) criterion
• Recompute distance matrices after every merge
• Construct the final Dendrogram

The data points are:
Point 1 → (2, 6)
Point 2 → (3, 4)
Point 3 → (3, 7)
Point 4 → (6, 2)
Point 5 → (7, 3)

This video clearly demonstrates how clusters are merged in the following order:
d(1,3) = 1
d(4,5) = 1.41
d(C13, C2) = 2.0
Final merge at distance 5.1

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Видео Single Linkage Hierarchical Clustering | Step-by-Step Solved Example | Agglomerative Clustering канала Mahesh Huddar

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16 февраля 2026 г. 20:33:08

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Mahesh Huddar

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