Improving support vector machine classification accuracy based on kernel parameters optimization
Improving support vector machine classification accuracy based on kernel parameters optimization
Lubna B. Mohammed,K. Raahemifar
2018 · DBLP: conf/springsim/MohammedR18
Spring Simulation Multiconference · 6 Citations
TLDR
The aim of this paper is to investigate the techniques that can be used to improve the classification accuracy of SVM based on kernel parameters optimization by implementing the analysis and comparison among different kernel parameters on different datasets.