Support Vector Machines
National Taiwan UniversityTaipei, Taiwan email@example.com
National Taiwan UniversityTaipei, Taiwan firstname.lastname@example.org
Machine learning algorithms have a tendency to over-fit. It is possible to achieve an arbitrarily low training error with some complex models, but the testing error may be high, because of poor generalization to unseen test instances. This is problematic, because the goal of classification is not to obtain good accuracy on known training data, but to predict unseen test instances correctly. Vapnik’s work  was motivated by this issue. His work started from a statistical derivation on linearly separable scenarios, and found that classifiers ...