Research Of Covering Algorithm In Lie Group Machine Learning

Lie Group Machine Learning(LML) inherit the advantages of manifold learning method and make full use of the Lie group's structure of algebraic and geometry in mathematics.Since it proposed,Lie Group Machine Learning method has been caused the specical concerning by many researchers.This paper is based on the theory of Lie Group Machine Learning(LML),it combines algebra model and the geometry model in Lie group machine learning and from the research we conclude the cover arithmetic of Lie Group Machine Learning.We also induct the Lie Group Machine Learning to the drug molecule design,including the application of drug effective model and molecule connect model. Through these examples,we get the application background of our new algorithms.Above all,the main characteristics of this paper are as follows:1.The theory of linear representations of group,coveting group in LML are given.2.The covering algorithm of LML is given,including simply connected covering algorithm,the solution of universal coveting group,multiply connected covering algorithm.3.The application of computer aided drug molecular design based on coveting algorithms are given,including the model of quantitative structure-activity relationships and drug molecular docking methods.