Skip to main content

Theory of Agglomerative Hierarchical Clustering

  • Book
  • © 2022

Overview

  • Provides new findings on theoretical aspects of agglomerative hierarchical clustering
  • Discusses theoretical foundations of some basic methods, e.g., single linkage, using a fuzzy concept
  • Considers new aspects such as network clustering, use of positive definite kernels, and the extended Ward method

Part of the book series: Behaviormetrics: Quantitative Approaches to Human Behavior (BQAHB, volume 15)

This is a preview of subscription content, log in via an institution to check access.

Access this book

eBook USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 119.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (6 chapters)

Keywords

About this book

This book discusses recent theoretical developments in agglomerative hierarchical clustering. The general understanding of agglomerative hierarchical clustering is that its theory was completed long ago and there is no room for further methodological studies, at least in its fundamental structure. This book has been planned counter to that view: it will show that there are possibilities for further theoretical studies and they will be not only for methodological interests but also for usefulness in real applications. When compared with traditional textbooks, the present book has several notable features. First, standard linkage methods and agglomerative procedure are described by a general algorithm in which dendrogram output is expressed by a recursive subprogram. That subprogram describes an abstract tree structure, which is used for a two-stage linkage method for a greater number of objects. A fundamental theorem for single linkage using a fuzzy graph is proved, which uncovers several theoretical features of single linkage. Other theoretical properties such as dendrogram reversals are discussed. New methods using positive-definite kernels are considered, and some properties of the Ward method using kernels are studied. Overall, theoretical features are discussed, but the results are useful as well for application-oriented users of agglomerative clustering.

 


Authors and Affiliations

  • University of Tsukuba, Tsukuba, Japan

    Sadaaki Miyamoto

About the author

Dr. Miyamoto was born in Osaka, Japan, in 1950. He received the B.S., M.S., and the Dr. Eng. degrees in Applied Mathematics and Physics Engineering from Kyoto University, Japan, in 1973, 1975, and 1978, respectively. He was Assistant Professor from 1980 to 1987 and Associate Professor from 1987 to 1990 in the University of Tsukuba. He was Professor with the Faculty of Engineering, the University of Tokushima, where he was working from 1990 to 1994. After working as Professor at the University of Tsukuba from 1994, he retired on March 31, 2016, and became Professor Emeritus from April 1, 2016.

His research interests include methodology for fuzzy systems and uncertainty modeling. In particular, he has been working on data clustering algorithms and related classification methods, multisets, rough sets, and algorithms for data mining. He is Member of the Japan Society of Fuzzy Theory and Systems, and Japanese Classification Society. He has served a number of internationalconferences as Chair, Co-chair, and Committee Member. He received excellent paper awards from the Japan Society of Fuzzy Theory and Systems in 1994 and 1999. He has published three books of which two are in English and the other in Japanese. He also has published one edited book and over 300 research papers. His papers/books have been cited more than 2,000 times. He became a fellow of International Fuzzy Systems Association in 2007. He was also elected to be a fellow of Japanese Classification Society in 2017.

Bibliographic Information

Publish with us