A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data (supervised learning), the algorithm outputs an optimal hyperplane which categorizes new examples.In which sense is the hyperplane obtained optimal? Let’s consider the following simple problem: For a linearly separable set of 2D-points which belong to one of two classes, find a separating straight line.
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