Incremental and Online Learning Algorithm for Regression Least Squares Support Vector Machine

Support vector machine is a learning technique based on the structural risk minimization principle,and it is also a class of regression method with good generalization ability.The paper firstly introduces the mathematical model of regression least squares support vector machine(LSSVM),and analyzes its property,then designs incremental and online learning algorithms based on LSSVM by the calculation formula of block matrix and kernel function matrix's property.The proposed learning algorithms fully utilizes the historical training results,reduces storage space and calculate time.Experimental results of simulation indicate the feasibility of the two learning algorithms.