SVMLSPex02.m Two Dimension SVM Problem, Two Class and Separable Situation Difference with SVMLSPex01.m: Take the Largrange Function (16)as object function insteads ||W||, so it need more time than SVMLSex01.m Method from Christopher J. C. Burges: "A Tutorial on Support Vector Machines for Pattern Recognition", page 9 Objective: min "f(A)=-sum(ai)+sum[sum(ai*yi*xi*aj*yj*xj)]/2" ,function (16) Subject to: sum{ai*yi}=0 ,function (15) and ai>=0 for any i, the particular set of constraints C2 (page 9, line14). The optimizing variables is "Lagrange Multipliers": A=[a1,a2,...,am],m is the number of total samples.

MATLAB函数参考手册.pdf

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