A novel sparse least squares support vector machines

DOI10.1155/2013/602341zbMath1299.68083OpenAlexW2061782044WikidataQ59027193 ScholiaQ59027193MaRDI QIDQ474428

Weidong Jiao, Xiao-Lei Xia, Kang Li, George W. Irwin

Publication date: 24 November 2014

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2013/602341

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (3)

Training sparse least squares support vector machines by the QR decomposition ⋮ Efficient model selection for sparse least-square SVMs ⋮ A pruning method of refining recursive reduced least squares support vector regression

Uses Software

• LIBSVM
• LS-SVMlab

Cites Work

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• Chaos control using least-squares support vector machines
• Bayesian Framework for Least-Squares Support Vector Machine Classifiers, Gaussian Processes, and Kernel Fisher Discriminant Analysis
• Improvements to Platt's SMO Algorithm for SVM Classifier Design
• A fast nonlinear model identification method
• Data mining with sparse grids

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