Smooth twin support vector regression | Neural Computing and Applications
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Oct 10, 2010 · We develop a novel SVR algorithm termed as smooth twin SVR (STSVR). The idea is to reformulate TSVR as a strongly convex problem, which results in unique ...
Jun 14, 2022 · Twin support vector regression (TSVR) is a useful extension of traditional support vector regression (SVR). As a new regression model, the basic idea of TSVR ...
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We develop a novel SVR algorithm termed as smooth twin SVR (STSVR). The idea is to reformulate TSVR as a strongly convex problem, which results in unique ...
This work develops a novel SVR algorithm termed as smooth twin SVR (STSVR), which is to reformulate TSVR as a strongly convex problem, which results in ...
The proposed model uses a smooth function to replace the loss function, which can change the model from the dual space solution to the original space solution.
Aug 29, 2024 · We introduce the guardian loss (G-loss), a novel loss function distinguished by its asymmetric, bounded, and smooth characteristics.
Missing: regression. | Show results with:regression.
As for regression problem, there are also many improved sup- port vector regression (SVR) algorithms, such as Smooth SVR [107–. 118], LS-SVR [119–130], the SMO ...
Feb 28, 2015 · Abstract. Twin support vector regression (TSVR) was proposed recently as a novel regressor that tries to find a pair of nonparallel planes, i.e. ...
Mar 2, 2023 · In this paper, we propose a novel robust twin support vector regression with smooth truncated Hε loss function, termed as THε-TSVR.
Mar 18, 2022 · Thus, this review presents a rigorous analysis of recent research in TWSVM and TSVR simultaneously mentioning their limitations and advantages.