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Data Clustering in C++: An Object-Oriented Approach (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

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Data clustering is a highly interdisciplinary field whose goal 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 papers and a number of books on data clustering have been published over the past 50 years. However, almost all papers and books focus on the theory of data clustering. There are few books that teach people how to implement data clustering algorithms.

This book was written for anyone who wants to implement data clustering algorithms and for those who want to implement new data clustering algorithms in a better way. Using object-oriented design and programming techniques, I have exploited 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 me through the development of the base data clustering classes and several popular data clustering algorithms.

This book focuses on how to implement data clustering algorithms in an object-oriented way. Other topics of clustering such as data pre-processing, data visualization, cluster visualization, and cluster interpretation are touched but not in detail. In this book, I used a direct and simple way to implement data clustering algorithms so that readers can understand the methodology easily. I also present the material in this book in a straightforward way. When I introduce a class, I present and explain the class method by method rather than present and go through the whole implementation of the class.

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. I have tested the code under Unix-like platforms (e.g., Ubuntu and Cygwin) and Microsoft Windows XP. The only requirements to compile the code are a modern C++ compiler and the Boost C++ libraries. This book is divided into three parts: Data Clustering and C++ Preliminaries, A C++ Data Clustering Framework, and Data Clustering Algorithms.

The first part reviews some basic concepts of data clustering, the unified modeling language, object-oriented programming in C++, and design patterns. The second part develops the data clustering base classes. The third part implements several popular data clustering algorithms. The content of each chapter is described briefly below.
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