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Hierarchical Clustering Techniques Explained by rameeshamalik.143 is a document available to read on EtoBox.
The document provides an overview of hierarchical clustering, focusing on its two main types: agglomerative and divisive. It explains the process of creating nested clusters using a proximity matrix and discusses various methods for measuring inter-cluster similarity, including single linkage, complete linkage, and group average linkage. The document also highlights the computational complexity of these algorithms and provides examples of single linkage clustering.
- Author
- rameeshamalik.143
- Language
- EN