Title of article
Rough ν-support vector regression
Author/Authors
Zhao، نويسنده , , Yongping and Sun، نويسنده , , Jianguo، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2009
Pages
6
From page
9793
To page
9798
Abstract
After combining the classical ν-SVR with the rough theory, we propose a rough ν-SVR. Double εs are utilized to construct the rough margin for rough ν-SVR instead of single ε for the classical ν-SVR, and this rough margin consisting of positive region, boundary region, and negative region yields the feasible set of the rough ν-SVR larger than that of the classical ν-SVR, which makes the objective function of the rough ν-SVR not more than that of the classical ν-SVR. This may lead to the improvement of the performance. Meantime, experimental results on benchmark data sets confirm the validation and feasibility of our proposed rough ν-SVR.
Keywords
Rough theory , Rough margin , ?-SVR
Journal title
Expert Systems with Applications
Serial Year
2009
Journal title
Expert Systems with Applications
Record number
2346734
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