A support vector machine ( SVM ) is a concept in computer science for a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis . The standard SVM takes a set of input data and predicts, for each given input, which of two possible classes the input is a member of, which makes the SVM a non- probabilistic binary linear classifier . Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that assigns new examples into one category or the other. An SVM model is a representation of the examples as points in space, mapped so that the examples of the separate categories are divided by a clear gap that is as wide as possible. New examples are then mapped into that same space and predicted to belong to a category based on which side of the gap they fall on. A Support Vector Machine (SVM) performs classification by constructing a...
Aresh T. Saharkhiz