title: [A post-processing method of classification rule on stellar spectra].
abstract: Automatic classification and analysis of observational data is of great significance along with the gradual implementation of LAMOST Survey, which will obtain a large number of spectra data. In classification rules extracted, there is often a great deal of redundancy which will reduce the classification efficiency and quality seriously. In the present paper, a post-processing method of star spectra classification rule based on predicate logic is presented by using predication to describe the classification rules and logical reasoning to eliminate redundant rules. In the end, some experimental results on LAMOST's stellar spectra data show that, with no classification accuracy reduction, the efficiency of auto classification is significantly improved.
authors.affiliation: School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan 030024, China. cjhjj@sohu.com
authors.forename: Jiang-Hui
authors.initials: JH
authors.lastname: Cai
authors.forename: Hai-Feng
authors.initials: HF
authors.lastname: Yang
authors.forename: Xu-Jun
authors.initials: XJ
authors.lastname: Zhao
authors.forename: Ji-Fu
authors.initials: JF
authors.lastname: Zhang