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An Efficient Sparse Twin Parametric Insensitive Support Vector Regression Model

This paper proposes a novel sparse twin parametric insensitive support vector regression (STPISVR) model, designed to enhance sparsity and improve generalization performance. Similar to twin parametric insensitive support vector regression (TPISVR), STPISVR constructs a pair of nonparallel parametri...

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Principais autores: Shuanghong Qu, Yushan Guo, Renato De Leone, Min Huang, Pu Li
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2025-07-01
Serier:Mathematics
Fag:
sparse twin parametric insensitive support vector regression (STPISVR)
sparsity
prediction speed
generalization performance
linear programming problem (LPP)
Karush–Kuhn–Tucker (KKT) conditions
Online adgang:https://www.mdpi.com/2227-7390/13/13/2206
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