Data Science, Machine Learning, Algorithms, Support Vector Machine, Supervised Learning.
boundary and margin for support vector classifiers, along with the corresponding support vectors. So, instead of trying to completely separate the vectors in into two classes, SMV make a trade-off. It allows for some vectors to fall inside the margin and on the wrong side of the decision boundary.