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Introduction to clustering large and high-dimensional data /
This book focuses on a few of the most important clustering algorithms, providing a detailed account of these major models in an information retrieval context. The beginning chapters introduce the classic algorithms in detail, while the later chapters describe clustering through divergences and show...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cambridge ; New York :
Cambridge University Press,
2007.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover; Half-title; Title; Copyright; Dedication; Contents; Foreword; Preface; 1 Introduction and motivation; 2 Quadratic k-means algorithm; 3 BIRCH; 4 Spherical k-means algorithm; 5 Linear algebra techniques; 6 Information theoretic clustering; 7 Clustering with optimization techniques; 8 k-means clustering with divergences; 9 Assessment of clustering results; 10 Appendix: Optimization and linear algebra background; 11 Solutions to selected problems; Bibliography; Index.