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GECCO
2003
Springer
15 years 5 months 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»
14 years 11 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
85
Voted
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
15 years 25 days 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...
73
Voted
ICPR
2010
IEEE
15 years 3 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Unsupervised Evaluation Methods Based on Local Gray-Intensity Variances for Binarization of Historical Documents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»
14 years 11 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