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» Symbolic regression in multicollinearity problems
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CEC
2011
IEEE
12 years 5 months ago
Trainer selection strategies for coevolving rank predictors
—Despite the range of applications and successes of evolutionary algorithms, expensive fitness computations often form a critical performance bottleneck. A preferred method of r...
Daniel L. Ly, Hod Lipson
GECCO
2008
Springer
175views Optimization» more  GECCO 2008»
13 years 6 months ago
Using differential evolution for symbolic regression and numerical constant creation
One problem that has plagued Genetic Programming (GP) and its derivatives is numerical constant creation. Given a mathematical formula expressed as a tree structure, the leaf node...
Brian M. Cerny, Peter C. Nelson, Chi Zhou
GECCO
2008
Springer
133views Optimization» more  GECCO 2008»
13 years 6 months ago
Using feature-based fitness evaluation in symbolic regression with added noise
Symbolic regression is a popular genetic programming (GP) application. Typically, the fitness function for this task is based on a sum-of-errors, involving the values of the depe...
Janine H. Imada, Brian J. Ross
GECCO
2010
Springer
169views Optimization» more  GECCO 2010»
13 years 8 months ago
Robust symbolic regression with affine arithmetic
We use affine arithmetic to improve both the performance and the robustness of genetic programming for symbolic regression. During evolution, we use affine arithmetic to analyze e...
Cassio Pennachin, Moshe Looks, João A. de V...
EUROGP
2008
Springer
105views Optimization» more  EUROGP 2008»
13 years 7 months ago
A Linear Estimation-of-Distribution GP System
We present N-gram GP, an estimation of distribution algorithm for the evolution of linear computer programs. The algorithm learns and samples the joint probability distribution of...
Riccardo Poli, Nicholas Freitag McPhee