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» Messy Genetic Algorithms for Subset Feature Selection
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EPS
1998
Springer
13 years 11 months ago
Acquisition of General Adaptive Features by Evolution
We investigate the following question. Do populations of evolving agents adapt only to their recent environment or do general adaptive features appear over time? We find statistica...
Dan Ashlock, John E. Mayfield
PR
2002
122views more  PR 2002»
13 years 7 months ago
High-order Fisher's discriminant analysis
This paper introduces a novel nonlinear extension of Fisher's classical linear discriminant analysis (FDA) known as high-order Fisher's discriminant analysis (HOFDA). Th...
Alejandro Sierra
CSB
2005
IEEE
143views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Multivariate gene selection: Does it help
When building predictors of disease state based on gene expression data, gene selection is performed in order to achieve a good performance and to identify a relevant subset of ge...
Carmen Lai, Marcel J. T. Reinders
GECCO
2007
Springer
163views Optimization» more  GECCO 2007»
14 years 1 months ago
Exploring medical data using visual spaces with genetic programming and implicit functional mappings
Two medical data sets (Breast cancer and Colon cancer) are investigated within a visual data mining paradigm through the unsupervised construction of virtual reality spaces using ...
Julio J. Valdés, Robert Orchard, Alan J. Ba...
NIPS
2007
13 years 8 months ago
Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
Maryam Mahdaviani, Tanzeem Choudhury