Wikipedia Support vector machine
supervised learning models used for classification and regression analysis. An SVM model is a representation of the training 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. Non-probabilistic binary linear classifier (some methods exist to use SVM in a probabilistic classification setting). Can be made non-linear with the "kernel trick" (implicitly mapping the inputs into high-dimensional feature spaces.)
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