About: Least-squares support vector machine

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Least-squares support-vector machines (LS-SVM) for statistics and in statistical modeling, are least-squares versions of support-vector machines (SVM), which are a set of related supervised learning methods that analyze data and recognize patterns, and which are used for classification and regression analysis. In this version one finds the solution by solving a set of linear equations instead of a convex quadratic programming (QP) problem for classical SVMs. Least-squares SVM classifiers were proposed by Johan Suykens and Joos Vandewalle. LS-SVMs are a class of kernel-based learning methods.

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rdfs:label	Least-squares support vector machine (en)
rdfs:comment	Least-squares support-vector machines (LS-SVM) for statistics and in statistical modeling, are least-squares versions of support-vector machines (SVM), which are a set of related supervised learning methods that analyze data and recognize patterns, and which are used for classification and regression analysis. In this version one finds the solution by solving a set of linear equations instead of a convex quadratic programming (QP) problem for classical SVMs. Least-squares SVM classifiers were proposed by Johan Suykens and Joos Vandewalle. LS-SVMs are a class of kernel-based learning methods. (en)
foaf:depiction
dcterms:subject	Classification algorithms Support vector machines Least squares Statistical classification
Wikipage page ID	26849824 (xsd:integer)
Wikipage revision ID	1116926548 (xsd:integer)
Link from a Wikipage to another Wikipage	Bayesian inference Bayesian probability Neural network Kernel methods Vapnik Johan Suykens Classification algorithms Saddle point Linear equation Statistical model Statistics Structural risk minimization Support vector machines Identity matrix Linear system Hierarchical classifier Prior probability Quadratic programming Regression analysis Hyperplane Lagrange multipliers Learning Support-vector machine Least squares Statistical classification Polynomial Radial basis function Statistical classification Linear Supervised learning Kernel function Lagrangian multipliers Least-squares
Link from a Wikipage to an external page	https://web.archive.org/web/20180627015707/https:/www.support-vector.net/ http://www.kernel-machines.org https://web.archive.org/web/20150513103825/http:/www.esat.kuleuven.be/sista/lssvmlab/ http://www.gaussianprocess.org/ http://dlib.net/ml.html%23krr_trainer
sameAs	Least-squares support vector machine Least-squares support vector machine
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has abstract	Least-squares support-vector machines (LS-SVM) for statistics and in statistical modeling, are least-squares versions of support-vector machines (SVM), which are a set of related supervised learning methods that analyze data and recognize patterns, and which are used for classification and regression analysis. In this version one finds the solution by solving a set of linear equations instead of a convex quadratic programming (QP) problem for classical SVMs. Least-squares SVM classifiers were proposed by Johan Suykens and Joos Vandewalle. LS-SVMs are a class of kernel-based learning methods. (en)
prov:wasDerivedFrom	wikipedia-en:Least-squares_support_vector_machine?oldid=1116926548&ns=0
page length (characters) of wiki page	16492 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:Least-squares_support_vector_machine
is Link from a Wikipage to another Wikipage of	Least-squares support-vector machine Support vector machine Least Squares Support Vector Machine Least squares support vector machine
is Wikipage redirect of	Least-squares support-vector machine Least Squares Support Vector Machine Least squares support vector machine
is foaf:primaryTopic of	wikipedia-en:Least-squares_support_vector_machine

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