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Support Vector Machines and Perceptrons - 9783319410623

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Item specifics

Condition
Brand new: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
Book Title
Support Vector Machines and Perceptrons
ISBN
9783319410623
Publication Year
2016
Type
Textbook
Format
Paperback
Language
English
Publication Name
Support Vector Machines and Perceptrons: Learning, Optimization, Classification, and Application to Social Networks
Item Height
235mm
Author
Rashmi Raghava, M.N. Murty
Publisher
Springer International Publishing A&G
Item Width
155mm
Subject
Computer Science
Item Weight
1825g
Number of Pages
95 Pages

About this product

Product Information

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.>

Product Identifiers

Publisher
Springer International Publishing A&G
ISBN-13
9783319410623
eBay Product ID (ePID)
223771740

Product Key Features

Author
Rashmi Raghava, M.N. Murty
Publication Name
Support Vector Machines and Perceptrons: Learning, Optimization, Classification, and Application to Social Networks
Format
Paperback
Language
English
Subject
Computer Science
Publication Year
2016
Type
Textbook
Number of Pages
95 Pages

Dimensions

Item Height
235mm
Item Width
155mm
Item Weight
1825g

Additional Product Features

Title_Author
M.N. Murty, Rashmi Raghava
Series Title
Springerbriefs in Computer Science
Country/Region of Manufacture
Switzerland

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  • GB 976952259
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