Support Vector Machine, Machine Learning, Artificial Intelligence, Data Science, Ambarish 224.
single, linear boundary, it may not work well for problems where the classes cannot be separated by a linear boundary. In such cases, a nonlinear SVM classifier can be used. The most commonly used technique to extend the linear SVM to a nonlinear SVM is the kernel trick. A. Explanation of the