Hierarchical Clustering | Agglomerative vs Divisive with examples

Hierarchical Clustering is an unsupervised learning technique that builds a hierarchy of clusters by either merging or splitting them. In this video, we’ll explore how hierarchical clustering works, its different linkage methods, and how it can be used to visualize data in a tree-like structure. This approach can be categorized into two types: Agglomerative (Bottom-up) and Divisive (Top-down).

00:00 – introduction
00:22 – Hierarchical Clustering
01:51 – types
02:26 – example

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Видео Hierarchical Clustering | Agglomerative vs Divisive with examples канала Gate Smashers