Könyv Support Vector Machines and Perceptrons M. N. Murty

Support Vector Machines and Perceptrons

Learning, Optimization, Classification, and Application to Social Networks

Nyelv: Angol
Kötés: Puha kötésű
Elérhetőség: Beszállítói készleten alacsony példányszámban
Küldés 13-18 napon belül
21 287 Ft
This work reviews the state of the art in SVM and perceptron classifiers. A Support Vector Machine (...

Információk a könyvről

Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2016
oldal
95
EAN
9783319410623
ISBN
3319410628
Enbook ID
10954085
Súly
1825
Méretek
155 x 235 x 6

Teljes leírás

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 the boundary and noisy vectors. Further, when the data are not linearly separable, tuning the coefficient of the regularization term becomes crucial. Even though SVMs have popularized the kernel trick, in most of the practical applications that are high-dimensional, linear SVMs are popularly used. The text examines applications to social and information networks. The work also discusses another popular linear classifier, the perceptron, and compares its performance with that of the SVM in different application areas.§

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