| Description |
1 online resource (xvi, 205 pages) : illustrations |
| Physical Medium |
polychrome |
| Description |
text file |
| Bibliography |
Includes bibliographical references (pages 189-201) and index. |
| Contents |
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. |
| Summary |
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. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Cluster analysis -- Data processing.
|
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Cluster analysis -- Data processing. |
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Cluster analysis -- Computer programs.
|
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Cluster analysis -- Computer programs. |
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Computer algorithms.
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Computer algorithms. |
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Dimensional analysis -- Data processing.
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Dimensional analysis. |
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Dimensional analysis -- Computer programs.
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Dimensional analysis -- Computer programs. |
| Genre/Form |
Electronic books.
|
| Other Form: |
Print version: Kogan, Jacob, 1954- Introduction to clustering large and high-dimensional data. Cambridge ; New York : Cambridge University Press, 2007 0521852676 9780521852678 (DLC) 2006024381 (OCoLC)70707967 |
| ISBN |
9780511257483 (electronic book) |
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0511257481 (electronic book) |
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0511254806 (electronic book ; Adobe Reader) |
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9780511254802 (electronic book ; Adobe Reader) |
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0521617936 (paper) |
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9780521617932 (paper) |
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0521852676 (cloth) |
|
9780521852678 (cloth) |
|
0511256981 (electronic book) |
|
9780511256981 (electronic book) |
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9780511256479 (electronic book) |
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0511256477 (electronic book) |
|
