Support Vector Machines
If you happened to have a classification, a regression or an outlier detection task, you might want to consider using Support Vector Machines (SVMs), a supervised learning model, that builds a line (hyperplane) to separate data into groups. SVM can perform not only linear classification but also effectively separate data in a non-linear, multi-dimensional space using the so called kernel trick which transfers data points into a high dimensional space. SVM is no new special fancy technique for machine learning, it exists since 1963.
Despite the fact that SVM is also applied for regression tasks, it is still more often used for classification.