Ashish Ghosh,
Satchidananda Dehuri,
Susmita Ghosh
Springer Berlin Heidelberg
2008e druk, 2008
9783540774662
Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
Specificaties
Gebonden, 162 blz.
|
Engels
Springer Berlin Heidelberg |
2008e druk, 2008
ISBN13: 9783540774662
Rubricering
Onderdeel van serie
Studies in Computational Intelligence
Verwachte levertijd ongeveer 9 werkdagen
Samenvatting
The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.
Specificaties
ISBN13:9783540774662
Taal:Engels
Bindwijze:gebonden
Aantal pagina's:162
Uitgever:Springer Berlin Heidelberg
Druk:2008
Inhoudsopgave
Genetic Algorithm for Optimization of Multiple Objectives in Knowledge Discovery from Large Databases.- Knowledge Incorporation in Multi-objective Evolutionary Algorithms.- Evolutionary Multi-objective Rule Selection for Classification Rule Mining.- Rule Extraction from Compact Pareto-optimal Neural Networks.- On the Usefulness of MOEAs for Getting Compact FRBSs Under Parameter Tuning and Rule Selection.- Classification and Survival Analysis Using Multi-objective Evolutionary Algorithms.- Clustering Based on Genetic Algorithms.
