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

Description

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, Front Cover Dedication Contents List of Figures List of Tables Preface I. Data Clustering and C++ Preliminaries 1. Introduction to Data Clustering 2. The Unified Modeling Language 3. Object-Oriented Programming and C++ 4. DesignPatterns 5. C++ Libraries and Tools II. A C++ Data Clustering Framework 6. The Clustering Library 7. Datasets 8. Clusters 9. Dissimilarity Measures 10. Clustering Algorithms 11. Utility Classes III. Data Clustering Algorithms 12. Agglomerative Hierarchical Algorithms 13. DIANA 14. The k-means Algorithm 15. The c-means Algorithm 16. The k-prototypes Algorithm 17. The Genetic k-modes Algorithm 18. The FSC Algorithm 19. The Gaussian Mixture Algorithm 20. A Parallel k-means Algorithm A. Exercises and Projects B. Listings C. Software Bibliography