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Center-based cluster analysis using inter-point distances.

Law, Shu Kei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 39-40). / Abstract also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Basic concept of clustering --- p.1 / Chapter 1.2 --- Main problems --- p.2 / Chapter 1.3 --- Review --- p.3 / Chapter 1.4 --- Newly proposed method --- p.7 / Chapter 1.5 --- Summary --- p.7 / Chapter 2 --- k-means clustering --- p.9 / Chapter 2.1 --- Algorithm of k-means clustering --- p.9 / Chapter 2.2 --- Selecting k in k-mcans clustering --- p.11 / Chapter 2.3 --- Disadvantages of k-means clustering --- p.12 / Chapter 3 --- Methodology and Algorithm --- p.14 / Chapter 3.1 --- Methodology and Algorithm --- p.14 / Chapter 3.2 --- Illustrative Example --- p.20 / Chapter 4 --- Simulation Study --- p.25 / Chapter 4.1 --- Simulation Plan --- p.25 / Chapter 4.2 --- Simulation Details --- p.27 / Chapter 4.3 --- Simulation Result --- p.30 / Chapter 4.4 --- Summary --- p.34 / Chapter 5 --- Conclusion and Further research --- p.36 / Bibliography --- p.38

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_326841
Date January 2009
ContributorsLaw, Shu Kei., Chinese University of Hong Kong Graduate School. Division of Statistics.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, vii, 40 leaves : ill. (some col.) ; 30 cm.
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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