Variable Selection for Kernel Classification

DOI10.1080/03610918.2010.534226zbMath1209.62147OpenAlexW2094354345MaRDI QIDQ3085308

N. Louw, S. J. Steel, Surette Bierman

Publication date: 31 March 2011

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2010.534226

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• ElemStatLearn

Cites Work

• ``Preconditioning for feature selection and regression in high-dimensional problems
• Variable selection in kernel Fisher discriminant analysis by means of recursive feature elimina\-tion
• On the ``degrees of freedom of the lasso
• Model Selection and Model Averaging
• Variable Selection for Support Vector Machines
• Regularization and Variable Selection Via the Elastic Net
• Soft margins for AdaBoost
• Random forests
• Training invariant support vector machines
• Gene selection for cancer classification using support vector machines

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