Train SVM models with different kernel functions. Visualize decision boundaries. Evaluate and compare model accuracy. Generate synthetic datasets (make_moons and make_blobs). Train SVM models with ...

For an another example, SVM works for only two class separation. It cannot separate more than two classes. That does not mean you cannot fit multi-class datasets to an SVM model, of course you can fit ...