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» Messy Genetic Algorithms for Subset Feature Selection
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JSS
2002
198views more  JSS 2002»
13 years 8 months ago
Automated discovery of concise predictive rules for intrusion detection
This paper details an essential component of a multi-agent distributed knowledge network system for intrusion detection. We describe a distributed intrusion detection architecture...
Guy G. Helmer, Johnny S. Wong, Vasant Honavar, Les...
TNN
2008
133views more  TNN 2008»
13 years 8 months ago
A General Wrapper Approach to Selection of Class-Dependent Features
In this paper, we argue that for a C-class classification problem, C 2-class classifiers, each of which discriminating one class from the other classes and having a characteristic ...
Lipo Wang, Nina Zhou, Feng Chu
GECCO
2000
Springer
112views Optimization» more  GECCO 2000»
14 years 20 hour ago
Code Compaction Using Genetic Algorithms
One method for compacting executable computer code is to replace commonly repeated sequences of instructions with macro instructions from a decoding dictionary. The size of the de...
Keith E. Mathias, Larry J. Eshelman, J. David Scha...
JMLR
2010
104views more  JMLR 2010»
13 years 3 months ago
Increasing Feature Selection Accuracy for L1 Regularized Linear Models
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
Abhishek Jaiantilal, Gregory Z. Grudic
GECCO
2008
Springer
158views Optimization» more  GECCO 2008»
13 years 9 months ago
Objective reduction using a feature selection technique
This paper introduces two new algorithms to reduce the number of objectives in a multiobjective problem by identifying the most conflicting objectives. The proposed algorithms ar...
Antonio López Jaimes, Carlos A. Coello Coel...