title: Prediction of Microporous Aluminophosphate AlPO4 -5 Based on Resampling Using Partial Least Squares and Logistic Discrimination.
abstract: In this paper, Partial Least Squares (PLS) regression and Logistic Discrimination (LD) are employed to predict the formation of microporous aluminophosphate AlPO4 -5 based on the database of AlPO synthesis, which aims to provide a useful guidance to the rational synthesis of microporous materials as well as other inorganic crystalline materials. To deal with the problem of class imbalance, four guided resampling methods considering not only the between-class imbalance but also the within-class imbalance are proposed. Experimental results indicate that the presented methods are competent for predicting the formation of microporous aluminophosphate AlPO4 -5. Specially, compared with some existing resampling methods, our proposed resampling methods exhibit much better predictive results.
authors.affiliation: School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China. qim801@nenu.edu.cn.
authors.forename: Miao
authors.initials: M
authors.lastname: Qi
authors.affiliation: Faculty of Chemistry, Northeast Normal University, Changchun 130117, China.
authors.forename: Yinghua
authors.initials: Y
authors.lastname: Lu
authors.affiliation: School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China.
authors.forename: Jianzhong
authors.initials: J
authors.lastname: Wang
authors.affiliation: School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China. kongjun@nenu.edu.cn.|Key Laboratory for Applied Statistics of MOE, Northeast Normal University, 130024, China. kongjun@nenu.edu.cn.
authors.forename: Jun
authors.initials: J
authors.lastname: Kong
keywords: Logistic discrimination; Microporous materials; Partial least squares; Resampling