Machine Learning, Support Vector Machine, Optimization, Data Science, Technology.
major advantage of the soft-margin SVM over the original hard-margin SVM is that the feasible region is never empty. That is, there is always going to be some solution, regardless of whether your training data is linearly separable or not. It’s one thing to write down an optimization problem. It’s