Support vector regression model with variant tolerance
نویسندگان
چکیده
Most works on Support Vector Regression (SVR) focus kernel or loss functions, with the corresponding support vectors obtained using a fixed-radius [Formula: see text]-tube, affording good predictive performance datasets. However, fixed radius limitation prevents adaptive selection of according to data distribution characteristics, compromising SVR-based methods. Therefore, this study proposes an “Alterable text]-Support Regression” ([Formula: text]-SVR) model by applying novel text], named text],” SVR model. Based point sparsity at each location, solves different text] position, and thus zoom-in zoom-out text]-tube changing its radius. Such variable strategy diminishes noise outliers in dataset, enhancing prediction text]-SVR we suggest non-deterministic algorithm iteratively solve complex problem optimizing associated every location. Extensive experimental results demonstrate that our approach can improve accuracy stability simulated real compared baseline
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ژورنال
عنوان ژورنال: Measurement & Control
سال: 2023
ISSN: ['2051-8730', '0020-2940']
DOI: https://doi.org/10.1177/00202940231180620