[PDF.11bp] Support Vector Machines and Perceptrons: Learning, Optimization, Classification, and Application to Social Networks (SpringerBriefs in Computer Science)

Support Vector Machines and Perceptrons: Learning, Optimization, Classification, and Application to Social Networks (SpringerBriefs in Computer Science)

[PDF.vf83] Support Vector Machines and Perceptrons: Learning, Optimization, Classification, and Application to Social Networks (SpringerBriefs in Computer Science)

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 | #6117913 in Books |  2016-08-18 |  2016-08-25 | Original language:English | PDF # 1 |  9.25 x.26 x6.10l,.0 | File type: PDF | 95 pages

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This work reviews the state of the art in SVM and perceptron classifiers. A Support Vector Machine (SVM) is easily the most popular tool for dealing with a variety of machine-learning tasks, including classification. SVMs are associated with maximizing the margin between two classes. The concerned optimization problem is a convex optimization guaranteeing a globally optimal solution. The weight vector associated with SVM is obtained by a linear combination of some of ...

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