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9781930708259

Data Mining: A Heuristic Approach

by ; ;
  • ISBN13:

    9781930708259

  • ISBN10:

    1930708254

  • Format: Hardcover
  • Copyright: 2002-01-01
  • Publisher: Idea Group Pub
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Summary

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. Data Mining: A Heuristic Approach will be a repository for the applications of these techniques in the area of data mining.

Table of Contents

Preface i
Part One: General Heuristics
From Evolution to Immune to Swarm to...? A Simple Introduction to Modern Heuristics
1(21)
Hussein A. Abbass
Approximating Proximity for Fast and Robust Distance-Based Clustering
22(26)
Vladimir Estivill-Castro
Michael Houle
Part Two: Evolutionary Algorithms
On the Use of Evolutionary Algorithms in Data Mining
48(24)
Erick Cantu-Paz
Chandrika Kamath
The discovery of interesting nuggets using heuristic techniques
72(25)
Beatriz de la Iglesia
Victor J. Rayward-Smith
Estimation of Distribution Algorithms for Feature Subset Selection in Large Dimensionality Domains
97(20)
Inaki Inza
Pedro Larranaga
Basilio Sierra
Towards the Cross-Fertillization of Multiple Heuristics: Evolving Teams of Local Bayesian Learners
117(26)
Jorge Muruzabal
Evolution of Spatial Data Templates for Object Classification
143(14)
Neil Dunstan
Michael de Raadt
Part Three: Genetic Programming
Genetic Programming as a Data-Mining Tool
157(17)
Peter W.H. Smith
A Building Block Approach to Genetic Programming for Rule Discovery
174(17)
A.P. Engelbrecht
Sonja Rouwhorst
L. Schoeman
Part Four: Ant Colony Optimization and Immune Systems
An Ant Colony Algorithm for Classification Rule Discovery
191(18)
Rafael S. Parpinelli
Heitor S. Lopes
Alex A. Freitas
Artificial Immune Systems: Using the Immune System as Inspiration for Data Mining
209(22)
Jon Timmis
Thomas Knight
aiNet: An Artificial Immune Network for Data Analysis
231(30)
Leandro Nunes de Castro
Fernando J. Von Zuben
Part Five: Parallel Data Mining
Parallel Data Mining
261(29)
David Taniar
J. Wenny Rahayu
About the Authors 290(7)
Index 297

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