Contact
How to shop
Delivery
Shopping guide
Least Squares Support Vector Machines
English
295 b
Delivery to Austria
Up to 30 days for returns
Customers also purchased
/
Paperback
10.89
€
/
Paperback
25.09
€
An examination of least squares support vector machines (LS-SVMs) which are reformulations to standard SVMs. LS-SVMs are closely related to regularization networks and Gaussian processes but additionally emphasize and exploit primal-dual interpretations from optimization theory. The authors explain the natural links between LS-SVM classifiers and kernel Fisher discriminant analysis. Bayesian inference of LS-SVM models is discussed, together with methods for imposing sparseness and employing robust statistics. The framework is further extended towards unsupervised learning by considering PCA analysis and its kernel version as a one-class modelling problem. This leads to new primal-dual support vector machine formulations for kernel PCA and kernel CCA analysis. Furthermore, LS-SVM formulations are given for recurrent networks and control. In general, support vector machines may pose heavy computational challenges for large data sets. For this purpose, a method of fixed size LS-SVM is proposed where the estimation is done in the primal space in relation to a Nystrom sampling with active selection of support vectors. The methods are illustrated with several examples.
About the book
English
Give this book today
It's easy
1 Add to cart and choose Deliver as present at the checkout 2 We'll send you a voucher 3 The book will arrive at the recipient's addressYou might also be interested in
/
Paperback
20.89
€
/
Hardback
50.39
€
/
Paperback
66.89
€
/
Paperback
13.59
€
/
Hardback
90.19
€
/
Paperback
17.09
€
Hi! I'm Libroamiko, your book advisor.
How can I help you?