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» Modified genetic algorithm for nonlinear data reconciliation
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KDD
2000
ACM
129views Data Mining» more  KDD 2000»
13 years 11 months ago
Evolutionary algorithms in data mining: multi-objective performance modeling for direct marketing
Predictive models in direct marketing seek to identify individuals most likely to respond to promotional solicitations or other intervention programs. While standard modeling appr...
Siddhartha Bhattacharyya
PAKDD
2007
ACM
158views Data Mining» more  PAKDD 2007»
14 years 1 months ago
Density-Sensitive Evolutionary Clustering
In this study, we propose a novel evolutionary algorithm-based clustering method, named density-sensitive evolutionary clustering (DSEC). In DSEC, each individual is a sequence of ...
Maoguo Gong, Licheng Jiao, Ling Wang, Liefeng Bo
GECCO
2003
Springer
117views Optimization» more  GECCO 2003»
14 years 25 days ago
A Method for Handling Numerical Attributes in GA-Based Inductive Concept Learners
This paper proposes a method for dealing with numerical attributes in inductive concept learning systems based on genetic algorithms. The method uses constraints for restricting th...
Federico Divina, Maarten Keijzer, Elena Marchiori
ACIIDS
2010
IEEE
171views Database» more  ACIIDS 2010»
13 years 10 months ago
Evolving Concurrent Petri Net Models of Epistasis
Abstract. A genetic algorithm is used to learn a non-deterministic Petri netbased model of non-linear gene interactions, or statistical epistasis. Petri nets are computational mode...
Michael Mayo, Lorenzo Beretta
ASC
2004
13 years 7 months ago
Extracting rules from trained neural network using GA for managing E-business
Theabilitytointelligentlycollect,manageandanalyzeinformationaboutcustomersandsellersisakeysourceofcompetitive advantage for an e-business. This ability provides an opportunity to ...
Atta Ebrahim E. ElAlfi, R. Haque, M. Esmel ElAlami