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Machine Learning
Hierarchical Clustering
Clustering that organises observations into a tree of nested groups.
Hierarchical clustering builds a sequence of nested clusters. Agglomerative methods begin with each observation as its own group and repeatedly merge the most similar clusters.
The resulting structure is displayed as a dendrogram, allowing analysts to inspect relationships at different levels. The approach is intuitive but can become computationally expensive on very large datasets.
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