Support Vector Machine, Machine Learning, Artificial Intelligence, Data Science, Ambarish 224.
overfitting: Because of the constraint on the margin, SVMs are quite robust to overfitting. B. Discussion of the disadvantages of using SVMs: Sensitivity to the choice of the kernel: The performance of an SVM is highly dependent on the choice of kernel function. Choosing the right kernel function