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» Model selection in genetic programming
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GECCO
2007
Springer
177views Optimization» more  GECCO 2007»
14 years 2 months ago
Evolving problem heuristics with on-line ACGP
Genetic Programming uses trees to represent chromosomes. The user defines the representation space by defining the set of functions and terminals to label the nodes in the trees. ...
Cezary Z. Janikow
GECCO
2007
Springer
159views Optimization» more  GECCO 2007»
14 years 2 months ago
A systemic computation platform for the modelling and analysis of processes with natural characteristics
Computation in biology and in conventional computer architectures seem to share some features, yet many of their important characteristics are very different. To address this, [1]...
Erwan Le Martelot, Peter J. Bentley, R. Beau Lotto
IPPS
2003
IEEE
14 years 2 months ago
Parallelisation of IBD Computation for Determining Genetic Disease Map
A number of software packages are available for the construction of comprehensive human genetic maps. In this paper we parallelize the widely used package Genehunter. We restrict ...
Nouhad J. Rizk
IWANN
2009
Springer
14 years 3 months ago
RCGA-S/RCGA-SP Methods to Minimize the Delta Test for Regression Tasks
Frequently, the number of input variables (features) involved in a problem becomes too large to be easily handled by conventional machine-learning models. This paper introduces a c...
Fernando Mateo, Dusan Sovilj, Rafael Gadea Giron&e...
HAIS
2009
Springer
14 years 1 months ago
Unsupervised Feature Selection in High Dimensional Spaces and Uncertainty
Developing models and methods to manage data vagueness is a current effervescent research field. Some work has been done with supervised problems but unsupervised problems and unce...
José Ramón Villar, María del ...