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19.2. Hierarchical Clustering by Abhishek Goyal is a document available to read on EtoBox.

Hierarchical clustering creates a clustering hierarchy represented as a dendrogram and is advantageous as it does not require pre-specifying the number of clusters or iterative refinement. It includes two main algorithms: agglomerative, which merges clusters from the bottom up, and divisive, which splits clusters from the top down. Various linkage methods such as single, complete, average, centroid, and Ward-linkage are used to determine the distance between clusters during the agglomerative process.

Author
Abhishek Goyal
Language
EN