Transformation of Input Domain for SVM in Regression Task

被引：3
|
作者：
Siminski, Krzysztof [1 ]
机构：
[1] Silesian Tech Univ, Inst Informat, PL-44100 Gliwice, Poland
来源：
MAN-MACHINE INTERACTIONS 3 | 2014年 / 242卷
关键词：
regression; support vector machine; neuro-fuzzy system; adaptive kernel; NEURO-FUZZY SYSTEM;
D O I：
10.1007/978-3-319-02309-0_46
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Support vector machines (SVM) and neuro-fuzzy systems (NFS) are efficient tools for regression tasks. The problem of the SVMs is the proper choice of kernel functions. Our idea is to transform the task's domain with NFS so that linear kernel can be applied. The paper is accompanied by numerical experiments.
引用
收藏
页码：423 / 430
页数：8
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