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GECCO
2003
Springer
14 years 28 days ago
Enhancing the Performance of GP Using an Ancestry-Based Mate Selection Scheme
The performance of genetic programming relies mostly on population-contained variation. If the population diversity is low then there will be a greater chance of the algorithm bein...
Rodney Fry, Andrew M. Tyrrell
IEICET
2007
68views more  IEICET 2007»
13 years 7 months ago
Generalization Error Estimation for Non-linear Learning Methods
Estimating the generalization error is one of the key ingredients of supervised learning since a good generalization error estimator can be used for model selection. An unbiased g...
Masashi Sugiyama
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
13 years 8 months ago
Threshold selecting: best possible probability distribution for crossover selection in genetic algorithms
The paper considers the problem of selecting individuals in the current population in Genetic Algorithms for crossover to find a solution of high fitness of a given combinatoria...
Jörg Lässig, Karl Heinz Hoffmann, Mihael...
ICPR
2010
IEEE
13 years 11 months ago
Unsupervised Evaluation Methods Based on Local Gray-Intensity Variances for Binarization of Historical Documents
Abstract--We attempt to evaluate the efficacy of six unsupervised evaluation method to tune Sauvola's threshold in optical character recognition (OCR) applications. We propose...
Marte Alejandro Ramírez-Ortegón, Raul Rojas
CORR
2006
Springer
94views Education» more  CORR 2006»
13 years 7 months ago
Fitness Uniform Optimization
Abstract-- In evolutionary algorithms, the fitness of a population increases with time by mutating and recombining individuals and by a biased selection of more fit individuals. Th...
Marcus Hutter, Shane Legg