A method for handling metabonomics data from liquid chromatography/mass spectrometry: combinational use of support vector machine recursive feature elimination, genetic algorithm and random forest for feature selection
Titel:
A method for handling metabonomics data from liquid chromatography/mass spectrometry: combinational use of support vector machine recursive feature elimination, genetic algorithm and random forest for feature selection
Auteur:
Lin, Xiaohui Wang, Quancai Yin, Peiyuan Tang, Liang Tan, Yexiong Li, Hong Yan, Kang Xu, Guowang