9 search results - page 2 / 2 » Nonlinear parametric regression in genetic programming |
PKDD
2010
Springer
13 years 2 months ago
2010
Springer
The foremost nonlinear dimensionality reduction algorithms provide an embedding only for the given training data, with no straightforward extension for test points. This shortcomin...
GECCO
2007
Springer
13 years 11 months ago
2007
Springer
In this paper, we analyze two general-purpose encoding types, trees and graphs systematically, focusing on trends over increasingly complex problems. Tree and graph encodings are ...
ICNC
2009
Springer
13 years 11 months ago
2009
Springer
The main purpose of this paper is to propose an incorporating a grammatical evolution (GE) into the genetic algorithm (GA), called GEGA, and apply it to estimate the compressive s...
GECCO
2007
Springer
13 years 11 months ago
2007
Springer
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...