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» Messy Genetic Algorithms for Subset Feature Selection
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GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
14 years 1 months ago
Evolving stochastic processes using feature tests and genetic programming
The synthesis of stochastic processes using genetic programming is investigated. Stochastic process behaviours take the form of time series data, in which quantities of interest v...
Brian J. Ross, Janine H. Imada
ALGORITHMICA
2006
74views more  ALGORITHMICA 2006»
13 years 8 months ago
Parallelizing Feature Selection
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...
KDD
2008
ACM
264views Data Mining» more  KDD 2008»
14 years 8 months ago
Stable feature selection via dense feature groups
Many feature selection algorithms have been proposed in the past focusing on improving classification accuracy. In this work, we point out the importance of stable feature selecti...
Lei Yu, Chris H. Q. Ding, Steven Loscalzo
EUROCAST
2003
Springer
105views Hardware» more  EUROCAST 2003»
14 years 1 months ago
A Self-adaptive Model for Selective Pressure Handling within the Theory of Genetic Algorithms
In this paper we introduce a new generic selection method for Genetic Algorithms. The main difference of this selection principle in contrast to conventional selection models is g...
Michael Affenzeller, Stefan Wagner 0002
EC
2000
171views ECommerce» more  EC 2000»
13 years 8 months ago
Building Blocks, Cohort Genetic Algorithms, and Hyperplane-Defined Functions
Building blocks are a ubiquitous feature at all levels of human understanding, from perception through science and innovation. Genetic algorithms are designed to exploit this prev...
John H. Holland