{"product_id":"least-squares-support-vector-machines-9789812381514-new","title":"Least Squares Support Vector Machines","description":"This book focuses on 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 Nystr","brand":"WORLD SCIENTIFIC PUB CO INC","offers":[{"title":"New","offer_id":51544086511906,"sku":"9789812381514-new","price":116.56,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0893\/4755\/5618\/files\/9789812381514.jpg?v=1776397983","url":"https:\/\/www.albakireads.com\/products\/least-squares-support-vector-machines-9789812381514-new","provider":"AlbakiReads","version":"1.0","type":"link"}