Data clustering in C++ an object-oriented approach
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 ha...
| Otros Autores: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Boca Raton :
CRC Press
2011.
Boca Raton, Fla. : 2011. |
| Edición: | 1st edition |
| Colección: | Chapman & Hall/CRC data mining and knowledge discovery series.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627901106719 |
Tabla de Contenidos:
- 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 Algorithm17. 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
