Pattern Recognition Algorithms for Data Mining

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CRC Press, 2004 M05 27 - 280 pages
Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, me
 

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Contents

Introduction
1
Multiscale Data Condensation
29
Unsupervised Feature Selection
59
Active Learning Using Support Vector Machine
83
Roughfuzzy Case Generation
103
Roughfuzzy Clustering
123
Rough SelfOrganizing Map
149
Classification Rule Generation and Evaluation using Modular Roughfuzzy MLP
165
Role of SoftComputing Tools in KDD
201
Data Sets Used in Experiments
211
References
215
Index
237
About the Authors
243
Copyright

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Page 223 - M. Klemettinen, H. Mannila, P. Ronkainen, H. Toivonen, and AI Verkamo. Finding interesting rules from large sets of discovered association rules.

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About the author (2004)

SANKAR K. PAL, PhD, is a Distinguished Scientist and founding head of the Machine Intelligence Unit at the Indian Statistical Institute, Calcutta. Professor Pal holds several PhDs and is a Fellow of the IEEE and IAPR.

SIMON C. K. SHIU, PhD, is Assistant Professor in the Department of Computing at Hong Kong Polytechnic University.

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