>> Yt = simlssvm({X,Y,type,gam,sig2,’RBF_kernel’,’preprocess’},{alpha,b},Xt);
ans =
0.0847
0.0378
1.9862
0.4688
0.3773
1.9832
0.2658
0.2515
1.5571
0.3130
The LS-SVM result can be displayed if the dimension of the input data is one or two.
>> plotlssvm({X,Y,type,gam,sig2,’RBF_kernel’,’preprocess’},{alpha,b});
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