title: An accurate density functional theory calculation for electronic excitation energies: the least-squares support vector machine.
abstract: Support vector machines (SVMs), as a novel type of learning machine, has been very successful in pattern recognition and function estimation problems. In this paper we introduce least-squares (LS) SVMs to improve the calculation accuracy of density functional theory. As a demonstration, this combined quantum mechanical calculation with LS-SVM correction approach has been applied to evaluate the electronic excitation energies of 160 organic molecules. The newly introduced LS-SVM approach reduces the root-mean-square deviation of the calculated electronic excitation energies of 160 organic molecules from 0.32 to 0.11 eV for the B3LYP/6-31G(d) calculation. Thus, the LS-SVM correction on top of B3LYP/6-31G(d) is a better method to correct electronic excitation energies and can be used as the approximation of experimental results which are impossible to obtain experimentally.
authors.affiliation: Institute of Functional Material Chemistry, Faculty of Chemistry, Northeast Normal University, Changchun, Jilin 130024, China.
authors.forename: Ting
authors.initials: T
authors.lastname: Gao
authors.forename: Shi-Ling
authors.initials: SL
authors.lastname: Sun
authors.forename: Li-Li
authors.initials: LL
authors.lastname: Shi
authors.forename: Hui
authors.initials: H
authors.lastname: Li
authors.forename: Hong-Zhi
authors.initials: HZ
authors.lastname: Li
authors.forename: Zhong-Min
authors.initials: ZM
authors.lastname: Su
authors.forename: Ying-Hua
authors.initials: YH
authors.lastname: Lu