Support Vector Machine

A supervised learning algorithm that finds the maximum-margin hyperplane separating two classes in feature space. SVMs with kernel tricks (RBF, polynomial) handle nonlinear classification. In robotics, SVMs are used for contact/no-contact classification from tactile signals and fault detection from vibration signatures. They have largely been superseded by neural networks for complex tasks.