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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 |
|---|---|
| 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 |
MARC
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| 100 | 1 | |a Kogan, Jacob, |d 1954- | |
| 245 | 1 | 0 | |a Introduction to clustering large and high-dimensional data / |c Jacob Kogan. |
| 260 | |a Cambridge ; |a New York : |b Cambridge University Press, |c 2007. | ||
| 300 | |a 1 online resource (xvi, 205 pages) : |b illustrations | ||
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| 504 | |a Includes bibliographical references (pages 189-201) and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a 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. | |
| 520 | |a 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 recent research for more advanced audiences. | ||
| 546 | |a English. | ||
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Cluster analysis |x Data processing. | |
| 650 | 0 | |a Cluster analysis |x Computer programs. | |
| 650 | 0 | |a Computer algorithms. | |
| 650 | 0 | |a Dimensional analysis |x Data processing. | |
| 650 | 0 | |a Dimensional analysis |x Computer programs. | |
| 650 | 0 | |a Algorithms. | |
| 650 | 6 | |a Classification automatique (Statistique) |x Informatique. | |
| 650 | 6 | |a Algorithmes. | |
| 650 | 6 | |a Analyse dimensionnelle |x Informatique. | |
| 650 | 7 | |a algorithms. |2 aat | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x General. |2 bisacsh | |
| 650 | 7 | |a Algorithms |2 fast | |
| 650 | 7 | |a Cluster analysis |x Computer programs |2 fast | |
| 650 | 7 | |a Cluster analysis |x Data processing |2 fast | |
| 650 | 7 | |a Computer algorithms |2 fast | |
| 650 | 7 | |a Dimensional analysis |x Computer programs |2 fast | |
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