title: Classification of the carcinogenicity of N-nitroso compounds based on support vector machines and linear discriminant analysis.
abstract: The support vector machine (SVM), as a novel type of learning machine, was used to develop a classification model of carcinogenic properties of 148 N-nitroso compounds. The seven descriptors calculated solely from the molecular structures of compounds selected by forward stepwise linear discriminant analysis (LDA) were used as inputs of the SVM model. The obtained results confirmed the discriminative capacity of the calculated descriptors. The result of SVM (total accuracy of 95.2%) is better than that of LDA (total accuracy of 89.8%).
authors.affiliation: Department of Chemistry, Lanzhou University, Lanzhou, Gansu 730000, China.
authors.forename: Feng
authors.initials: F
authors.lastname: Luan
authors.forename: Ruisheng
authors.initials: R
authors.lastname: Zhang
authors.forename: Chunyan
authors.initials: C
authors.lastname: Zhao
authors.forename: Xiaojun
authors.initials: X
authors.lastname: Yao
authors.forename: Mancang
authors.initials: M
authors.lastname: Liu
authors.forename: Zhide
authors.initials: Z
authors.lastname: Hu
authors.forename: Botao
authors.initials: B
authors.lastname: Fan
mesh_terms: D001185:Artificial Intelligence; D002273:Carcinogens / Q000145:classification*; D003198:Computer Simulation; D019992:Databases as Topic; D016002:Discriminant Analysis; D016014:Linear Models; D008962:Models, Theoretical; D009603:Nitroso Compounds / Q000145:classification*
chemical_list: D002273:Carcinogens; D009603:Nitroso Compounds