Introduction to clustering large and high-dimensional data:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge [u.a.]
Cambridge Univ. Press
2007
|
| Ausgabe: | 1. publ. |
| Schlagworte: | |
| Online-Zugang: | Publisher description Table of contents only Contributor biographical information Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references (p. 189-201) and index |
| Beschreibung: | XVI, 205 S. Ill., graph. Darst. 24 cm |
| ISBN: | 9780521852678 9780521617932 0521852676 0521617936 |
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| 245 | 1 | 0 | |a Introduction to clustering large and high-dimensional data |c Jacob Kogan |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a Cambridge [u.a.] |b Cambridge Univ. Press |c 2007 | |
| 300 | |a XVI, 205 S. |b Ill., graph. Darst. |c 24 cm | ||
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| 500 | |a Includes bibliographical references (p. 189-201) and index | ||
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| 650 | 7 | |a Algoritmen |2 gtt | |
| 650 | 4 | |a Analyse dimensionnelle - Informatique | |
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| 650 | 4 | |a Classification automatique (Statistique) - Informatique | |
| 650 | 4 | |a Classification automatique (Statistique) - Logiciels | |
| 650 | 7 | |a Clusteranalyse |2 gtt | |
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Datensatz im Suchindex
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| adam_text | INTRODUCTION TO CLUSTERING LARGE AND HIGH-DIMENSIONAL DATA JACOB KOGAN
UNIVERSITY OF MARYLAND, BALTIMORE COUNTY CAMBRIDGE UNIVERSITY PRESS
CONTENTS FOREWORD BY MICHAEL W. BERRY PAGE XI PREFACE XIII 1
INTRODUCTION AND MOTIVATION 1 1.1 A WAY TO EMBED ASCII DOCUMENTS INTO A
FINITE DIMENSIONAL EUCLIDEAN SPACE 3 1.2 CLUSTERING AND THIS BOOK 5 1.3
BIBLIOGRAPHIC NOTES 6 2 QUADRATIC &-MEANS ALGORITHM 9 2.1 CLASSICAL
BATCH FC-MEANS ALGORITHM 10 2.1.1 QUADRATIC DISTANCE AND CENTROIDS 12
2.1.2 BATCH FC-MEANS CLUSTERING ALGORITHM 13 2.1.3 BATCH A:-MEANS:
ADVANTAGES AND DEFICIENCIES 14 2.2 INCREMENTAL ALGORITHM 21 2.2.1
QUADRATIC FUNCTIONS 21 2.2.2 INCREMENTAL /C-MEANS ALGORITHM 25 2.3
QUADRATIC A MEANS: SUMMARY 29 2.3.1 NUMERICAL EXPERIMENTS WITH QUADRATIC
FC-MEANS 29 2.3.2 STABLE PARTITIONS 31 2.3.3 QUADRATIC /C-MEANS 35 2.4
SPECTRAL RELAXATION * 37 2.5 BIBLIOGRAPHIC NOTES 38 3 BIRCH 41 3.1
BALANCED ITERATIVE REDUCING AND CLUSTERING ALGORITHM 41 VU BIRCH-LIKE
FC-MEANS BIBLIOGRAPHIC NOTES CONTENTS 44 49 SPHERICAL FC-MEANS ALGORITHM
4.1 SPHERICAL BATCH &-MEANS ALGORITHM 4.1.1 SPHERICAL BATCH FC-MEANS:
ADVANTAGES AND DEFICIENCIES 4.1.2 COMPUTATIONAL CONSIDERATIONS 4.2
SPHERICAL TWO-CLUSTER PARTITION OF ONE-DIMENSIONAL DATA 4.2.1
ONE-DIMENSIONAL LINE VS. THE UNIT CIRCLE 4.2.2 OPTIMAL TWO CLUSTER
PARTITION ON THE UNIT CIRCLE 4.3 SPHERICAL BATCH AND INCREMENTAL
CLUSTERING ALGORITHMS 4.3.1 FIRST VARIATION FOR SPHERICAL /C-MEANS 4.3.2
SPHERICAL INCREMENTAL ITERATIONS-COMPUTATIONS COMPLEXITY 4.3.3 THE
PING-PONG ALGORITHM 4.3.4 QUADRATIC AND SPHERICAL &-MEANS 4.4
BIBLIOGRAPHIC NOTES 5 LINEAR ALGEBRA TECHNIQUES 5.1 TWO APPROXIMATION
PROBLEMS 5.2 5.3 5.4 5.5 NEAREST LINE PRINCIPAL DIRECTIONS DIVISIVE
PARTITIONING 5.3.1 PRINCIPAL DIRECTION DIVISIVE PARTITIONING (PDDP)
5.3.2 SPHERICAL PRINCIPAL DIRECTIONS DIVISIVE PARTITIONING (SPDDP) 5.3.3
CLUSTERING WITH PDDP AND SPDDP LARGEST EIGENVECTOR 5.4.1 POWER METHOD
5.4.2 AN APPLICATION: HUBS AND AUTHORITIES BIBLIOGRAPHIC NOTES
INFORMATION THEORETIC CLUSTERING 6.1 KULLBACK-LEIBLER DIVERGENCE
FC-MEANS WITH KULLBACK-LEIBLER DIVERGENCE NUMERICAL EXPERIMENTS DISTANCE
BETWEEN PARTITIONS BIBLIOGRAPHIC NOTES 51 51 53 55 57 57 60 64 65 68 69
71 72 73 73 74 77 77 80 82 87 89 91 91 94 96 98 99 CONTENTS IX 7
CLUSTERING WITH OPTIMIZATION TECHNIQUES 101 7.1* OPTIMIZATION FRAMEWORK
102 7.2 SMOOTHING &-MEANS ALGORITHM 103 7.3 CONVERGENCE 109 7.4
NUMERICAL EXPERIMENTS 114 7.5 BIBLIOGRAPHIC NOTES 122 8 K-MEANS
CLUSTERING WITH DIVERGENCES 125 8.1 BREGMAN DISTANCE 125 8.2
^-DIVERGENCES 128 8.3 CLUSTERING WITH ENTROPY-LIKE DISTANCES 132 8.4
BIRCH-TYPE CLUSTERING WITH ENTROPY-LIKE DISTANCES 135 8.5 NUMERICAL
EXPERIMENTS WITH (V, /X) A;-MEANS 140 8.6 SMOOTHING WITH ENTROPY-LIKE
DISTANCES 144 8.7 NUMERICAL EXPERIMENTS WITH (V, /Z) SMOKA 146 8.8
BIBLIOGRAPHIC NOTES 152 9 ASSESSMENT OF CLUSTERING RESULTS 155 9.1
INTERNAL CRITERIA 155 9.2 EXTERNAL CRITERIA 156 9.3 BIBLIOGRAPHIC NOTES
160 10 APPENDIX: OPTIMIZATION AND LINEAR ALGEBRA BACKGROUND 161 10.1
EIGENVALUES OF A SYMMETRIC MATRIX 161 10.2 LAGRANGE MULTIPLIERS 163 10.3
ELEMENTS OF CONVEX ANALYSIS 164 10.3.1 CONJUGATE FUNCTIONS 166 10.3.2
ASYMPTOTIC CONES 169 10.3.3 ASYMPTOTIC FUNCTIONS 173 10.3.4 SMOOTHING
176 10.4 BIBLIOGRAPHIC NOTES 178 11 SOLUTIONS TO SELECTED PROBLEMS 179
BIBLIOGRAPHY 189 INDEX 203
|
| adam_txt |
INTRODUCTION TO CLUSTERING LARGE AND HIGH-DIMENSIONAL DATA JACOB KOGAN
UNIVERSITY OF MARYLAND, BALTIMORE COUNTY CAMBRIDGE UNIVERSITY PRESS
CONTENTS FOREWORD BY MICHAEL W. BERRY PAGE XI PREFACE XIII 1
INTRODUCTION AND MOTIVATION 1 1.1 A WAY TO EMBED ASCII DOCUMENTS INTO A
FINITE DIMENSIONAL EUCLIDEAN SPACE 3 1.2 CLUSTERING AND THIS BOOK 5 1.3
BIBLIOGRAPHIC NOTES 6 2 QUADRATIC &-MEANS ALGORITHM 9 2.1 CLASSICAL
BATCH FC-MEANS ALGORITHM 10 2.1.1 QUADRATIC DISTANCE AND CENTROIDS 12
2.1.2 BATCH FC-MEANS CLUSTERING ALGORITHM 13 2.1.3 BATCH A:-MEANS:
ADVANTAGES AND DEFICIENCIES 14 2.2 INCREMENTAL ALGORITHM 21 2.2.1
QUADRATIC FUNCTIONS 21 2.2.2 INCREMENTAL /C-MEANS ALGORITHM 25 2.3
QUADRATIC A MEANS: SUMMARY 29 2.3.1 NUMERICAL EXPERIMENTS WITH QUADRATIC
FC-MEANS 29 2.3.2 STABLE PARTITIONS 31 2.3.3 QUADRATIC /C-MEANS 35 2.4
SPECTRAL RELAXATION * 37 2.5 BIBLIOGRAPHIC NOTES 38 3 BIRCH 41 3.1
BALANCED ITERATIVE REDUCING AND CLUSTERING ALGORITHM 41 VU BIRCH-LIKE
FC-MEANS BIBLIOGRAPHIC NOTES CONTENTS 44 49 SPHERICAL FC-MEANS ALGORITHM
4.1 SPHERICAL BATCH &-MEANS ALGORITHM 4.1.1 SPHERICAL BATCH FC-MEANS:
ADVANTAGES AND DEFICIENCIES 4.1.2 COMPUTATIONAL CONSIDERATIONS 4.2
SPHERICAL TWO-CLUSTER PARTITION OF ONE-DIMENSIONAL DATA 4.2.1
ONE-DIMENSIONAL LINE VS. THE UNIT CIRCLE 4.2.2 OPTIMAL TWO CLUSTER
PARTITION ON THE UNIT CIRCLE 4.3 SPHERICAL BATCH AND INCREMENTAL
CLUSTERING ALGORITHMS 4.3.1 FIRST VARIATION FOR SPHERICAL /C-MEANS 4.3.2
SPHERICAL INCREMENTAL ITERATIONS-COMPUTATIONS COMPLEXITY 4.3.3 THE
"PING-PONG" ALGORITHM 4.3.4 QUADRATIC AND SPHERICAL &-MEANS 4.4
BIBLIOGRAPHIC NOTES 5 LINEAR ALGEBRA TECHNIQUES 5.1 TWO APPROXIMATION
PROBLEMS 5.2 5.3 5.4 5.5 NEAREST LINE PRINCIPAL DIRECTIONS DIVISIVE
PARTITIONING 5.3.1 PRINCIPAL DIRECTION DIVISIVE PARTITIONING (PDDP)
5.3.2 SPHERICAL PRINCIPAL DIRECTIONS DIVISIVE PARTITIONING (SPDDP) 5.3.3
CLUSTERING WITH PDDP AND SPDDP LARGEST EIGENVECTOR 5.4.1 POWER METHOD
5.4.2 AN APPLICATION: HUBS AND AUTHORITIES BIBLIOGRAPHIC NOTES
INFORMATION THEORETIC CLUSTERING 6.1 KULLBACK-LEIBLER DIVERGENCE
FC-MEANS WITH KULLBACK-LEIBLER DIVERGENCE NUMERICAL EXPERIMENTS DISTANCE
BETWEEN PARTITIONS BIBLIOGRAPHIC NOTES 51 51 53 55 57 57 60 64 65 68 69
71 72 73 73 74 77 77 80 82 87 89 91 91 94 96 98 99 CONTENTS IX 7
CLUSTERING WITH OPTIMIZATION TECHNIQUES 101 7.1* OPTIMIZATION FRAMEWORK
102 7.2 SMOOTHING &-MEANS ALGORITHM 103 7.3 CONVERGENCE 109 7.4
NUMERICAL EXPERIMENTS 114 7.5 BIBLIOGRAPHIC NOTES 122 8 K-MEANS
CLUSTERING WITH DIVERGENCES 125 8.1 BREGMAN DISTANCE 125 8.2
^-DIVERGENCES 128 8.3 CLUSTERING WITH ENTROPY-LIKE DISTANCES 132 8.4
BIRCH-TYPE CLUSTERING WITH ENTROPY-LIKE DISTANCES 135 8.5 NUMERICAL
EXPERIMENTS WITH (V, /X) A;-MEANS 140 8.6 SMOOTHING WITH ENTROPY-LIKE
DISTANCES 144 8.7 NUMERICAL EXPERIMENTS WITH (V, /Z) SMOKA 146 8.8
BIBLIOGRAPHIC NOTES 152 9 ASSESSMENT OF CLUSTERING RESULTS 155 9.1
INTERNAL CRITERIA 155 9.2 EXTERNAL CRITERIA 156 9.3 BIBLIOGRAPHIC NOTES
160 10 APPENDIX: OPTIMIZATION AND LINEAR ALGEBRA BACKGROUND 161 10.1
EIGENVALUES OF A SYMMETRIC MATRIX 161 10.2 LAGRANGE MULTIPLIERS 163 10.3
ELEMENTS OF CONVEX ANALYSIS 164 10.3.1 CONJUGATE FUNCTIONS 166 10.3.2
ASYMPTOTIC CONES 169 10.3.3 ASYMPTOTIC FUNCTIONS 173 10.3.4 SMOOTHING
176 10.4 BIBLIOGRAPHIC NOTES 178 11 SOLUTIONS TO SELECTED PROBLEMS 179
BIBLIOGRAPHY 189 INDEX 203 |
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| dewey-tens | 510 - Mathematics |
| discipline | Informatik Mathematik Wirtschaftswissenschaften |
| discipline_str_mv | Informatik Mathematik Wirtschaftswissenschaften |
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| open_access_boolean | |
| owner | DE-91G DE-BY-TUM DE-634 DE-706 DE-29T DE-384 |
| owner_facet | DE-91G DE-BY-TUM DE-634 DE-706 DE-29T DE-384 |
| physical | XVI, 205 S. Ill., graph. Darst. 24 cm |
| publishDate | 2007 |
| publishDateSearch | 2007 |
| publishDateSort | 2007 |
| publisher | Cambridge Univ. Press |
| record_format | marc |
| spelling | Kogan, Jacob 1954- Verfasser (DE-588)140237283 aut Introduction to clustering large and high-dimensional data Jacob Kogan 1. publ. Cambridge [u.a.] Cambridge Univ. Press 2007 XVI, 205 S. Ill., graph. Darst. 24 cm txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references (p. 189-201) and index Algorithmes Algoritmen gtt Analyse dimensionnelle - Informatique Analyse dimensionnelle - Logiciels Classification automatique (Statistique) - Informatique Classification automatique (Statistique) - Logiciels Clusteranalyse gtt Datenverarbeitung Cluster analysis Data processing Cluster analysis Computer programs Computer algorithms Dimensional analysis Data processing Dimensional analysis Computer programs Cluster-Analyse (DE-588)4070044-6 gnd rswk-swf Computerunterstütztes Verfahren (DE-588)4139030-1 gnd rswk-swf Dimensionsanalyse (DE-588)4133116-3 gnd rswk-swf Cluster-Analyse (DE-588)4070044-6 s Computerunterstütztes Verfahren (DE-588)4139030-1 s DE-604 Dimensionsanalyse (DE-588)4133116-3 s http://www.loc.gov/catdir/enhancements/fy0664/2006024381-d.html Publisher description http://www.loc.gov/catdir/enhancements/fy0664/2006024381-t.html Table of contents only http://www.loc.gov/catdir/enhancements/fy0733/2006024381-b.html Contributor biographical information HEBIS Datenaustausch Darmstadt application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016320710&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Kogan, Jacob 1954- Introduction to clustering large and high-dimensional data Algorithmes Algoritmen gtt Analyse dimensionnelle - Informatique Analyse dimensionnelle - Logiciels Classification automatique (Statistique) - Informatique Classification automatique (Statistique) - Logiciels Clusteranalyse gtt Datenverarbeitung Cluster analysis Data processing Cluster analysis Computer programs Computer algorithms Dimensional analysis Data processing Dimensional analysis Computer programs Cluster-Analyse (DE-588)4070044-6 gnd Computerunterstütztes Verfahren (DE-588)4139030-1 gnd Dimensionsanalyse (DE-588)4133116-3 gnd |
| subject_GND | (DE-588)4070044-6 (DE-588)4139030-1 (DE-588)4133116-3 |
| title | Introduction to clustering large and high-dimensional data |
| title_auth | Introduction to clustering large and high-dimensional data |
| title_exact_search | Introduction to clustering large and high-dimensional data |
| title_exact_search_txtP | Introduction to clustering large and high-dimensional data |
| title_full | Introduction to clustering large and high-dimensional data Jacob Kogan |
| title_fullStr | Introduction to clustering large and high-dimensional data Jacob Kogan |
| title_full_unstemmed | Introduction to clustering large and high-dimensional data Jacob Kogan |
| title_short | Introduction to clustering large and high-dimensional data |
| title_sort | introduction to clustering large and high dimensional data |
| topic | Algorithmes Algoritmen gtt Analyse dimensionnelle - Informatique Analyse dimensionnelle - Logiciels Classification automatique (Statistique) - Informatique Classification automatique (Statistique) - Logiciels Clusteranalyse gtt Datenverarbeitung Cluster analysis Data processing Cluster analysis Computer programs Computer algorithms Dimensional analysis Data processing Dimensional analysis Computer programs Cluster-Analyse (DE-588)4070044-6 gnd Computerunterstütztes Verfahren (DE-588)4139030-1 gnd Dimensionsanalyse (DE-588)4133116-3 gnd |
| topic_facet | Algorithmes Algoritmen Analyse dimensionnelle - Informatique Analyse dimensionnelle - Logiciels Classification automatique (Statistique) - Informatique Classification automatique (Statistique) - Logiciels Clusteranalyse Datenverarbeitung Cluster analysis Data processing Cluster analysis Computer programs Computer algorithms Dimensional analysis Data processing Dimensional analysis Computer programs Cluster-Analyse Computerunterstütztes Verfahren Dimensionsanalyse |
| url | http://www.loc.gov/catdir/enhancements/fy0664/2006024381-d.html http://www.loc.gov/catdir/enhancements/fy0664/2006024381-t.html http://www.loc.gov/catdir/enhancements/fy0733/2006024381-b.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016320710&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT koganjacob introductiontoclusteringlargeandhighdimensionaldata |