About this document
Hierarchical Clustering Techniques by Arul Kumar Venugopal is a document available to read on EtoBox.
Hierarchical clustering is an unsupervised machine learning algorithm that groups similar objects into clusters. There are two main types: agglomerative, which starts with each object as a separate cluster and merges them sequentially, and divisive, which starts with all objects in one cluster and splits them sequentially. Agglomerative clustering is more popular and works by iteratively merging the closest pair of clusters based on a defined proximity measure until only one cluster remains, producing a hie
- Author
- Arul Kumar Venugopal
- Language
- EN