About: An iterative algorithm learning the maximal margin classifier

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	A simple learning algorithm for maximal margin classifiers (also support vector machines with quadratic cost function) is proposed. We build our iterative algorithm on top of the Schlesinger-Kozinec algorithm (S-K-algorithm) from 1981 which finds a maximal margin hyperplane with a given precision for separable data. We suggest a generalization of the S-K-algorithm (i) to the non-linear case using kernel functions and (ii) for non-separable data. The requirement in memory storage is linear to the data. This property allows the proposed algorithm to be used for large training problems. The resulting algorithm is simple to implement and as the experiments showed competitive to the state-of-the-art algorithms. The implementation of the algorithm in Matlab is available. We tested the algorithm on the problem aiming at recognition poor quality numerals. A simple learning algorithm for maximal margin classifiers (also support vector machines with quadratic cost function) is proposed. We build our iterative algorithm on top of the Schlesinger-Kozinec algorithm (S-K-algorithm) from 1981 which finds a maximal margin hyperplane with a given precision for separable data. We suggest a generalization of the S-K-algorithm (i) to the non-linear case using kernel functions and (ii) for non-separable data. The requirement in memory storage is linear to the data. This property allows the proposed algorithm to be used for large training problems. The resulting algorithm is simple to implement and as the experiments showed competitive to the state-of-the-art algorithms. The implementation of the algorithm in Matlab is available. We tested the algorithm on the problem aiming at recognition poor quality numerals. (en)
Title	An iterative algorithm learning the maximal margin classifier An iterative algorithm learning the maximal margin classifier (en)
skos:prefLabel	An iterative algorithm learning the maximal margin classifier An iterative algorithm learning the maximal margin classifier (en)
skos:notation	RIV/68407700:21230/03:03091285!RIV/2004/GA0/212304/N
http://linked.open.../vavai/riv/strany	1985 ; 1996
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(GA102/00/1679), Z(MSM 212300013)
http://linked.open...iv/cisloPeriodika	9
http://linked.open...vai/riv/dodaniDat	2004
http://linked.open...aciTvurceVysledku	Hlaváč, Václav Franc, Vojtěch
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta elektrotechnická
http://linked.open...dnocenehoVysledku	597998
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/03:03091285
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Kernel functions;Linear classifier;Pattern recognition;Suppervised learning;Support Vector Machines (en)
http://linked.open.../riv/klicoveSlovo	Support Vector Machines Pattern recognition Kernel functions Linear classifier Suppervised learning
http://linked.open...odStatuVydavatele	NL - Nizozemsko
http://linked.open...ontrolniKodProRIV	[215A67176A5A]
http://linked.open...i/riv/nazevZdroje	Pattern recognition
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...vavai/riv/projekt	Geometry and appearance of a three-dimensional scene from a huge collection of two-dimensional images
http://linked.open...UplatneniVysledku	2003
http://linked.open...v/svazekPeriodika	36
http://linked.open...iv/tvurceVysledku	Hlaváč, Václav Franc, Vojtěch
http://linked.open...n/vavai/riv/zamer	http://linked.opendata.cz/resource/domain/vavai/zamer/MSM%20212300013
issn	0031-3203
number of pages	12 (xsd:int)
http://localhost/t...ganizacniJednotka	21230

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