Data mining : a heuristic approach / [edited by] Hussein A. Abbass, Ruhul A. Sarker, Charles S. Newton
- Bib ID:
- 1550592
- Format:
- Book
- Online Version:
- Table of contents
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- Description:
-
- Hershey, PA ; London : Idea Group Pub./Information Science Publishing, c2002
- iv, 300 p. : ill. ; 26 cm.
- ISBN:
- 1930708254
- Full contents:
-
- Machine derived contents note: Part One: General Heuristics
- Chapter 1: From Evolution to Immune to Swarm to...?
- A Simple Introduction to Modern Heuristics 1
- Hussein A. Abbass, University of New South Wales, Australia
- Chapter 2: Approximating Proximityfor Fast andRobust
- Distance-Based Clustering 22
- Vladimir Estivill-Castro, University of Newcastle, Australia
- Michael Houle, University of Sydney, Australia
- Part Two: Evolutionary Algorithms
- Chapter3: On the Use of Evolutionary Algorithmsin Data Mining 48
- Erick Cantu-Paz, Lawrence Livermore National Laboratory, USA
- Chandrika Kamath, Lawrence Livermore National Laboratory, USA
- Chapter 4: The discovery of interesting nuggets using heuristic techniques 72
- Beatriz de la Iglesia, University of East Anglia, UK
- Victor J. Rayward-Smith, University of East Anglia, UK
- Chapter5: Estimation of Distribution Algorithms forFeature Subset
- Selection in Large Dimensionality Domains 97
- Ifiaki Inza, University of the Basque Country, Spain
- Pedro Larranaga, University of the Basque Country, Spain
- Basilio Sierra, University of the Basque Country, Spain
- Chapter 6: Towards the Cross-Fertilization of Multiple Heuristics:
- Evolving Teams of Local Bayesian Learners 117
- Jorge Muruzdbal, Universidad Rey Juan Carlos, Spain
- Chapter 7: Evolution of SpatialData Templates for Object Classification 143
- Neil Dunstan, University of New England, Australia
- Michael de Raadt, University of Southern Queensland, Australia
- Part Three: Genetic Programming
- Chapter 8: Genetic Programming as a Data-Mining Tool 157
- Peter W.H. Smith, City University, UK
- Chapter 9: A Building BlockApproach to Genetic Programming
- for Rule Discovery 174
- A.P. Engelbrecht, University of Pretoria, South Africa
- Sonja Rouwhorst, Vrije Universiteit Amsterdam, The Netherlands
- L. Schoeman, University of Pretoria, South Africa
- Part Four: Ant Colony Optimization and Immune Systems
- Chapter 10: An Ant Colony Algorithm for Classification Rule Discovery 191
- Rafael S. Parpinelli, Centro Federal de Educacao Tecnologica do Parana, Brazil
- Heitor S. Lopes, Centro Federal de Educacao Tecnologica do Parana, Brazil
- Alex A. Freitas, Pontificia Universidade Catolica do Parana, Brazil
- Chapter 11: ArtificialImmune Systems: Using the Immune System
- as Inspiration forDataMining 209
- Jon Timmis, University of Kent at Canterbury, UK
- Thomas Knight, University of Kent at Canterbury, UK
- Chapter 12: aiNet: An Artificial Immune Network for Data Analysis 231
- Leandro Nunes de Castro, State University of Campinas, Brazil
- Fernando J. Von Zuben, State University of Campinas, Brazil
- Part Five: Parallel Data Mining
- Chapter 13: Parallel Data Mining 261
- David Taniar, Monash University, Australia
- J. Wenny Rahayu, La Trobe University, Australia.
- Notes:
- Includes bibliographical references and index.
- Subject:
- Other authors/contributors:
- Copyright:
-
In Copyright
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Copyright status was determined using the following information:
- Material type:
- Literary Dramatic Musical
- Published status:
- Published
- Publication date:
- 2002
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