TSVMPath: Fast Regularization Parameter Tuning Algorithm for Twin Support Vector Machine

Twin support vector machine (TSVM) has attracted much attention in the field of machine learning with good generalization ability and computational performance. However, the conventional grid search method is very time-consuming to obtain the optimal regularization parameter. To address this problem...

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Veröffentlicht in:	Neural processing letters Jg. 54; H. 6; S. 5457 - 5482
Hauptverfasser:	Zhou, Kanglei, Zhang, Qiyang, Li, Juntao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.12.2022 Springer Nature B.V
Schlagworte:	Accuracy Algorithms Artificial Intelligence Classification Complex Systems Computational Intelligence Computer Science Design Efficiency Lagrange multiplier Machine learning Optimization Optimization models Parameters Quadratic programming Regularization Search methods Support vector machines Tuning Statistical machine learning Regularized solution path Parameter tuning algorithm Twin support vector machine
ISSN:	1370-4621, 1573-773X
Online-Zugang:	Volltext
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