a study on sigmoid kernels for svm and the training of non-psd
Date Issued
2005-03-06
Date
2005-03-06
Author(s)
DOI
20060927122853789664
Abstract
In this paper, we discuss
such non-PSD kernels through the viewpoint of separability. Results help to validate
the possible use of non-PSD kernels. One example shows that the sigmoid kernel matrix
is conditionally positive definite (CPD) in certain parameters & thus are valid kernels
there...
Subjects
Sigmoid Kernel
non-Positive Semi-Definite Kernel
Sequential Minimal Optimization
Support Vector Machine
Publisher
臺北市:國立臺灣大學資訊工程學系
Type
journal article
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