Comments on Quasi-Linear Support Vector Machine for Nonlinear Classification

被引:1
作者
Kamata, Sei-ichiro [1 ]
Mine, Tsunenori [2 ]
机构
[1] Waseda Univ, Grad Sch Informat Product & Syst, Kitakyushu Shi 808 0135, Japan
[2] Kyushu Univ, Fac Informat Sci & Elect Engn, Fukuoka Shi 8190395, Japan
关键词
support vector machine; classification; machine learning;
D O I
10.1587/transfun.2022EAL2051
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In 2014, the above paper entitled `Quasi-Linear Support Vector Machine for Nonlinear Classification' was published by Zhou, et al. [1]. They proposed a quasi-linear kernel function for support vector machine (SVM). However, in this letter, we point out that this proposed kernel function is a part of multiple kernel functions generated by well-known multiple kernel learning which is proposed by Bach, et al. [2] in 2004. Since then, there have been a lot of related papers on multiple kernel learning with several applications [3]. This letter verifies that the main kernel function proposed by Zhou, et al. [1] can be derived using multiple kernel learning algorithms [3]. In the kernel construction, Zhou, et al. [1] used Gaussian kernels, but the multiple kernel learning had already discussed the locality of additive Gaussian kernels or other kernels in the framework [4], [5]. Especially additive Gaussian or other kernels were discussed in tutorial at major international conference ECCV2012 [6]. The authors did not discuss these matters.
引用
收藏
页码:1444 / 1445
页数:2
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