Hey,
The 'fitcsvm' function in MATLAB is used for training a support vector machine (SVM) for binary classification. However, if 'fitcsvm' is not supported for code generation, you can use the lower-level functions that fitcsvm uses internally.
Here’s an example of how you can do this:
% Assume X is your N-by-P matrix of predictors, and Y is your N-by-1 vector of responses
X = 10; % your predictor matrix
Y = 20; % your response vector
% Convert the responses to +1 and -1 for the SVM
Y(Y == 0) = -1;
% Set up the SVM problem
H = 0.5 * (X' * X);
f = -Y;
A = -diag(Y) * X;
b = -ones(size(Y));
lb = zeros(size(X, 2), 1);
% Solve the SVM problem using quadprog
alpha = quadprog(H, f, A, b, [], [], lb);
% Compute the bias term
bias = mean(Y - X * (X' * alpha));
% Now you can classify new data using sign(Xnew * (X' * alpha) + bias)
This code does essentially the same thing as fitcsvm, but uses 'quadprog' to solve the SVM problem directly.
Thanks!
