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» Automated Learning of Rules Using Genetic Operators
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PKDD
1999
Springer
103views Data Mining» more  PKDD 1999»
13 years 12 months ago
An Evolutionary Algorithm Using Multivariate Discretization for Decision Rule Induction
Abstract. We describe EDRL-MD, an evolutionary algorithm-based system, for learning decision rules from databases. The main novelty of our approach lies in dealing with continuous ...
Wojciech Kwedlo, Marek Kretowski
CAISE
2004
Springer
14 years 1 months ago
Towards a Semi-Automated Approach to Intermodel Transformation
This paper introduces an extension to the hypergraph data model used in the AutoMed data intergration approach that allows constraints common in static data modelling languages to ...
Michael Boyd, Peter McBrien
ILP
1999
Springer
13 years 12 months ago
Rule Evaluation Measures: A Unifying View
Numerous measures are used for performance evaluation in machine learning. In predictive knowledge discovery, the most frequently used measure is classification accuracy. With new...
Nada Lavrac, Peter A. Flach, Blaz Zupan
IWCLS
2007
Springer
14 years 1 months ago
On Lookahead and Latent Learning in Simple LCS
Learning Classifier Systems use evolutionary algorithms to facilitate rule- discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most c...
Larry Bull
GECCO
2006
Springer
186views Optimization» more  GECCO 2006»
13 years 11 months ago
Genetic algorithms for action set selection across domains: a demonstration
Action set selection in Markov Decision Processes (MDPs) is an area of research that has received little attention. On the other hand, the set of actions available to an MDP agent...
Greg Lee, Vadim Bulitko