Robust Support Vector Machine With Asymmetric Truncated Generalized Pinball Loss

The support vector machine (SVM) with pinball loss (Pin-SVM) can handle noise sensitivity and instability to re-sampling but loses sparsity. To solve this limitation, SVM with a generalized pinball loss that incorporates an insensitive zone (GP-SVM) was proposed. The GP-SVM can handle sparsity by op...

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Veröffentlicht in:	IEEE access Jg. 12; S. 155696 - 155717
Hauptverfasser:	Suppalap, Siwakon, Wangkeeree, Rabian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Asymmetry Classification Convex functions difference of convex functions programming Fasteners generalized pinball loss Noise Noise sensitivity Optimization methods pinball loss Programming Robustness Sensitivity Sparsity Support vector machine Support vector machines Training Vectors
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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