Multiclass Classification and Feature Selection Based on Least Squares Regression with Large Margin

DOI10.1162/neco_a_01116zbMath1476.62147DBLPjournals/neco/ZhaoWW18OpenAlexW2884224972WikidataQ90316137 ScholiaQ90316137MaRDI QIDQ5157256

Siqi Wang, Zheng Wang, Hai-feng Zhao

Publication date: 12 October 2021

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/neco_a_01116

zbMATH Keywords

classificationleast squares regression

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Linear regression; mixed models (62J05) Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• LIBSVM
• CMU PIE
• AR face
• COIL-20
• PRMLT

Cites Work

• Theoretical comparison between the Gini Index and Information Gain criteria
• Multiple rank multi-linear SVM for matrix data classification
• Wrappers for feature subset selection
• Principal component analysis.
• Support-vector networks
• Stable local dimensionality reduction approaches
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• 10.1162/153244303322753670
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• The elements of statistical learning. Data mining, inference, and prediction
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