| Description |
1 online resource (441 pages) : illustrations |
| Series |
Chapman & Hall/CRC data mining and knowledge discovery series |
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Chapman & Hall/CRC data mining and knowledge discovery series.
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| Contents |
Introduction ; Sugato Basu, Ian Davidson, and Kiri L. Wagstaff ; Semisupervised Clustering with User Feedback ; David Cohn, Rich Caruana, and Andrew Kachites McCallum ; Gaussian Mixture Models with Equivalence Constraints ; Noam Shental, Aharon Bar-Hillel, Tomer Hertz, and Daphna Weinshall ; Pairwise Constraints as Priors in Probabilistic Clustering ; Zhengdong Lu and Todd K. Leen ; Clustering with Constraints: A Mean-Field Approximation Perspective ; Tilman Lange, Martin H. Law, Anil K. Jain, and J.M. Buhmann ; Constraint-Driven Co-Clustering of 0/1 Data ; Ruggero G. Pensa, Céline Robardet, and Jean-François Boulicaut ; On Supervised Clustering for Creating Categorization Segmentations ; Charu Aggarwal, Stephen C |
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Gates, and Philip Yu ; Clustering with Balancing Constraints ; Arindam Banerjee and Joydeep Ghosh ; Using Assignment Constraints to Avoid Empty Clusters in k-Means Clustering ; A. Demiriz, K.P. Bennett, and P.S. Bradley ; Collective Relational Clustering ; Indrajit Bhattacharya and Lise Getoor ; Nonredundant Data Clustering ; David Gondek ; Joint Cluster Analysis of Attribute Data and Relationship Data ; Martin Ester, Rong Ge, Byron J |
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Gao, Zengjian Hu, and Boaz Ben-moshe ; Correlation Clustering ; Nicole Immorlica and Anthony Wirth ; Interactive Visual Clustering for Relational Data ; Marie desJardins, James MacGlashan, and Julia Ferraioli ; Distance Metric Learning from Cannot-Be-Linked Example Pairs with Application to Name Disambiguation ; Satoshi Oyama and Katsumi Tanaka ; Privacy-Preserving Data Publishing: A Constraint-Based Clustering Approach ; Anthony K.H. Tung, Jiawei Han, Laks V.S. Lakshmanan, and Raymond T. Ng ; Learning with Pairwise Constraints for Video Object Classification ; Rong Yan, Jian Zhang, Jie Yang, and Alexander G. Hauptmann ; References ; Index |
| Summary |
Covers the capabilities and limitations of constrained clustering. This title presents various types of constraints for clustering, describes useful variations of the standard problem of clustering under constraints, and applies clustering with constraints to relational, bibliographic, and video data |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Print version record |
| Subject |
Cluster analysis -- Data processing
|
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Data mining.
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Computer algorithms.
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Cluster Analysis
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Electronic Data Processing
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Data Mining
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Algorithms
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algorithms.
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MATHEMATICS -- Probability & Statistics -- General.
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Cluster analysis -- Data processing
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Computer algorithms
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Data mining
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| Form |
Electronic book
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| Author |
Basu, Sugato.
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Davidson, Ian, 1971-
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Wagstaff, Kiri Lou.
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| ISBN |
9781584889977 |
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1584889977 |
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9781584889960 |
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1584889969 |
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