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» Feature Subset Selection Using a Genetic Algorithm
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ICML
2010
IEEE
13 years 10 months ago
Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes
Approximate dynamic programming has been used successfully in a large variety of domains, but it relies on a small set of provided approximation features to calculate solutions re...
Marek Petrik, Gavin Taylor, Ronald Parr, Shlomo Zi...
ICCS
2004
Springer
14 years 2 months ago
Designing Digital Circuits for the Knapsack Problem
Abstract. Multi Expression Programming (MEP) is a Genetic Programming variant that uses linear chromosomes for solution encoding. A unique feature of MEP is its ability of encoding...
Mihai Oltean, Crina Grosan, Mihaela Oltean
BMCBI
2006
126views more  BMCBI 2006»
13 years 9 months ago
Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass ge
Background: Due to the large number of genes in a typical microarray dataset, feature selection looks set to play an important role in reducing noise and computational cost in gen...
Chia Huey Ooi, Madhu Chetty, Shyh Wei Teng
SBBD
2000
168views Database» more  SBBD 2000»
13 years 10 months ago
Fast Feature Selection Using Fractal Dimension
Dimensionalitycurse and dimensionalityreduction are two issues that have retained highinterest for data mining, machine learning, multimedia indexing, and clustering. We present a...
Caetano Traina Jr., Agma J. M. Traina, Leejay Wu, ...
SMA
2005
ACM
125views Solid Modeling» more  SMA 2005»
14 years 2 months ago
One-dimensional selections for feature-based data exchange
In the parametric feature based design paradigm, most features possess arguments that are subsets of the boundary of the current model, subsets defined interactively by user sele...
Ari Rappoport, Steven N. Spitz, Michal Etzion