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Does fitcsvm use a kernel by default?

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Muhammad Haziq Kamarul Azman
Hello,
I was wondering: when we call fitcsvm to generate an SVM model without specifying a KernelFunction argument, does it find the hyperplane with or without a kernel?
I tried running it without specifying anything and with specifying a linear kernel (which I suspect is either a default MATLAB choice or is the SVM without a kernel) and obtained the same results in term of confusion matrices.
If I understand correctly, there should be a difference between a simple hyperplane cutting through the data in parameter space and the hyperplane/surface cutting through the projection of the data onto a feature space. As the linear kernel is defined as xi'xj (in the manpage for fitcsvm) then this would introduce a mapping/projection, wouldn't it?

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