Data Clustering in C++

An Object-Oriented Approach

Guojun Gan

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English

Chapman & Hall/CRC
28 March 2011

Probability & statistics; Object-oriented programming (OOP); Data capture & analysis; Data mining

Data clustering is a highly interdisciplinary field, the goal of which is to divide a set of objects into homogeneous groups such that objects in the same group are similar and objects in different groups are quite distinct. Thousands of theoretical papers and a number of books on data clustering have been published over the past 50 years. However, few books exist to teach people how to implement data clustering algorithms. This book was written for anyone who wants to implement or improve their data clustering algorithms.

Using object-oriented design and programming techniques, Data Clustering in C++ exploits the commonalities of all data clustering algorithms to create a flexible set of reusable classes that simplifies the implementation of any data clustering algorithm. Readers can follow the development of the base data clustering classes and several popular data clustering algorithms. Additional topics such as data pre-processing, data visualization, cluster visualization, and cluster interpretation are briefly covered. This book is divided into three parts-- Data Clustering and C++ Preliminaries: A review of basic concepts of data clustering, the unified modeling language, object-oriented programming in C++, and design patterns A C++ Data Clustering Framework: The development of data clustering base classes Data Clustering Algorithms: The implementation of several popular data clustering algorithms A key to learning a clustering algorithm is to implement and experiment the clustering algorithm. Complete listings of classes, examples, unit test cases, and GNU configuration files are included in the appendices of this book as well as in the CD-ROM of the book. The only requirements to compile the code are a modern C++ compiler and the Boost C++ libraries.

By: Guojun Gan
Imprint: Chapman & Hall/CRC
Country of Publication: United States
Volume: 20
Dimensions: Height: 234mm, Width: 156mm, Spine: 36mm
Weight: 907g
ISBN: 9781439862230
ISBN 10: 1439862230
Pages: 520
Publication Date: 28 March 2011
Audience: Professional and scholarly , College/higher education , Undergraduate , Primary
Format: Hardback
Publisher's Status: Active

Data Clustering and C++ Preliminaries. Data Clustering Framework. Data Clustering Algorithms.

Guojun Gan, Manulife Financial, Toronto, Canada