Data mining a heuristic approach
Title:
Data mining a heuristic approach
Author:
Abbass, Hussein A.
ISBN:
9781591400110
Publication Information:
Hershey, Pa. : IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA), c2002.
Physical Description:
electronic texts (iv, 300 p. : ill.) : digital files.
Contents:
1. From evolution to immune to swarm to? A simple introduction to modern heuristics / Jay Rodstein, Katherine Watters -- 2. Approximating proximity to fast and robust distance-based clustering / Vladimir Estivill-Castro, Michael Houle -- 3. On the use of evolutionary algorithms in data mining / Erick Cantu-Paz -- 4. The discovery of interesting nuggets using heuristic techniques / Beatriz de la Iglesia, Victor Rayward-Smith -- 5. Estimation of distribution algorithms for feature subset selection in large dimensionality domains / Inaki Inza, Pedro Larranaga, Basilio Sierra -- 6. Towards the cross-fertilization of multiple heuristics / Jorge Muruzabal -- 7. Evolution of spatial data templates for object classification / Neil Dunstan, Michael de Raadt-- 8. Genetic programming as a data-mining tool / Peter Smith -- 9. A building block approach to genetic programming for rule discovery / A. Engelbrecht, L. Schoeman, Sonja Rouwhorst -- 10. An ant colony algorithm for classification rule discovery / Rafael Parpinelli, Heitor Lopes, Alex Freitas -- 11. Artificial immune systems / Jonathan Timmis, Thomas Knight -- 12. aiNet / Leandro Nunes de Castro, Fernando Von Zuben -- 13. Parallel data mining / David Taniar, J. Rahayu.
Abstract:
Real life problems are known to be messy, dynamic and multi-objective, and involve high levels of uncertainty and constraints. Because traditional problem-solving methods are no longer capable of handling this level of complexity, heuristic search methods have attracted increasing attention in recent years for solving such problems. Inspired by nature, biology, statistical mechanics, physics and neuroscience, heuristics techniques are used to solve many problems where traditional methods have failed. This book will be a repository for the applications of these techniques in the area of data mining.
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Electronic Access:
Chapter PDFs via platform: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-93070-825-9