“…SVM has high generalization performance using a hyperplane, providing localized and global solutions, while conventional neural networks often converge on only the local minima. Its feasibility for chemical analysis was previously reported, e.g., for identifying components or structure such as mass spectra (Bern et al, 2004;Hilario et al, 2006;Somorjai et al, 2003), FT-IR spectra (Ferrão et al, 2007), NIR spectra (Chauchard et al, 2004;Chen et al, 2006;Devos et al, 2009), and Raman spectra (Gaus et al, 2006;Ishikawa and Gulick, 2013;Rösch et al, 2005;Sattlecker et al, 2010). However, its feasibility for analyzing radiation spectra is yet to be studied.…”