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Support vector machine
In machine learning , support vector machines ( SVMs , also support vector networks [ 1 ] ) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis . The basic SVM takes a set of input data and predicts, for each given input, which of two possible classes forms the output, making it a non- probabilistic binary linear classifier . Given a set of training examples, each marked as belonging to one of two categories, a SVM training algorithm builds a model that assigns new examples into one category or the other.
Data Mining
ML
GA