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EUROGP
2000
Springer
107views Optimization» more  EUROGP 2000»
13 years 8 months ago
Using Factorial Experiments to Evaluate the Effect of Genetic Programming Parameters
Abstract. Statistical techniques for designing and analysing experiments are used to evaluate the individual and combined effects of genetic programming parameters. Three binary cl...
Robert Feldt, Peter Nordin
AIR
2005
122views more  AIR 2005»
13 years 4 months ago
The Genetic Kernel Support Vector Machine: Description and Evaluation
The Support Vector Machine (SVM) has emerged in recent years as a popular approach to the classification of data. One problem that faces the user of an SVM is how to choose a kerne...
Tom Howley, Michael G. Madden
GECCO
2004
Springer
140views Optimization» more  GECCO 2004»
13 years 10 months ago
Keeping the Diversity with Small Populations Using Logic-Based Genetic Programming
We present a new method of Logic-Based Genetic Programming (LBGP). Using the intrinsic mechanism of backtracking in Prolog, we utilize large individual programs with redundant clau...
Ken Taniguchi, Takao Terano
CORR
2006
Springer
153views Education» more  CORR 2006»
13 years 4 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...
GECCO
2006
Springer
181views Optimization» more  GECCO 2006»
13 years 8 months ago
Designing safe, profitable automated stock trading agents using evolutionary algorithms
Trading rules are widely used by practitioners as an effective means to mechanize aspects of their reasoning about stock price trends. However, due to the simplicity of these rule...
Harish Subramanian, Subramanian Ramamoorthy, Peter...