论文信息 - Support Vector Regression Estimation Based on Non-uniform Lost Function

Support Vector Regression Estimation Based on Non-uniform Lost Function

The performances of support vector regression estimation were analyzed. It was found that the insensitive factor epsiv can affect the performance of support vector regression estimation significantly. The noise inside the sample data should be considered in determining the insensitive factor epsiv when support vector regression was employed. A novel support vector regression based on non-uniform lost function (NLF-SVR) was proposed to deal with different noise data density function in different region. The formulation and algorithms of computing NLF-SVR were given. The test example showed that the outcomes of NLF-SVR are better than that of conventional SVR. NLF-SVR can be applied in physiological systems modeling

Xiaofeng Song | Tong Zhou | Huanping Zhang

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