Data Clustering in C++: An Object-Oriented Approach

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 downloadable resources. The only requirements to compile the code are a modern C++ compiler and the Boost C++ libraries.