title: Prediction of retention indices for frequently reported compounds of plant essential oils using multiple linear regression, partial least squares, and support vector machine.
abstract: Retention indices for frequently reported compounds of plant essential oils on three different stationary phases were investigated. Multivariate linear regression, partial least squares, and support vector machine combined with a new variable selection approach called random-frog recently proposed by our group, were employed to model quantitative structure-retention relationships. Internal and external validations were performed to ensure the stability and predictive ability. All the three methods could obtain an acceptable model, and the optimal results by support vector machine based on a small number of informative descriptors with the square of correlation coefficient for cross validation, values of 0.9726, 0.9759, and 0.9331 on the dimethylsilicone stationary phase, the dimethylsilicone phase with 5% phenyl groups, and the PEG stationary phase, respectively. The performances of two variable selection approaches, random-frog and genetic algorithm, are compared. The importance of the variables was found to be consistent when estimated from correlation coefficients in multivariate linear regression equations and selection probability in model spaces.
authors.affiliation: Research Center of Modernization of Traditional Chinese Medicine, Central South University, Changsha, PR China.
authors.forename: Jun
authors.initials: J
authors.lastname: Yan
authors.forename: Jian-Hua
authors.initials: JH
authors.lastname: Huang
authors.forename: Min
authors.initials: M
authors.lastname: He
authors.forename: Hong-Bing
authors.initials: HB
authors.lastname: Lu
authors.forename: Rui
authors.initials: R
authors.lastname: Yang
authors.forename: Bo
authors.initials: B
authors.lastname: Kong
authors.forename: Qing-Song
authors.initials: QS
authors.lastname: Xu
authors.forename: Yi-Zeng
authors.initials: YZ
authors.lastname: Liang
mesh_terms: D000465:Algorithms; D016018:Least-Squares Analysis; D016014:Linear Models; D015999:Multivariate Analysis; D009822:Oils, Volatile / Q000032:analysis*; D010944:Plants / Q000737:chemistry*; D012044:Regression Analysis
chemical_list: D009822:Oils, Volatile
keywords: Plant essential oils; Quantitative structure-retention relationships; Random-frog; Retention index