How to simulate the given optimization problem related to SVM in MATLAB ?

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Hello all, I am trying to optimize the following problem in MATLAB. It is related to multiclass classification using SVM. There are total 16 classes (𝓁 is from 1 to 16).
where is a column vector of dimension , is also a column vector of dimension , is matrix of dimension , is row vector of and is the Gaussian radial basis function, where is the variance.
The main moto in this optmization problem is to obtain the value of α for 16 different 𝓁 i.e., I have to obtain .
With the help from Torsten (Level 9 MVP) and Matt J (Level 10 MVP), I had understood how to solve the function inside two summation.
My query is for 16 different b each of dimension , how to solve this optimization problem.
Any help in this regard will be highly appreciated.
  4 个评论
Catalytic
Catalytic 2023-3-22
编辑:Catalytic 2023-3-22
So is this approach correct ?
Probably. But why not just try it, rather than waiting hours and hours for other people to weight in? You could have verified by now whether it works.
Torsten
Torsten 2023-3-23
编辑:Torsten 2023-3-23
The code above is not for l=1, but a general code for arbitrary dimension of alpha.
You only need to fill in the correct values for K, b and C instead of the phantasy values used here:
K=rand(3);
K=K*K.';
b=rand(3,1)-0.5;
C=5;

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