About: Pattern Recognition by Probabilistic Neural Networks - Mixtures of Product Components versus Mixtures of Dependence Trees

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	We compare two probabilistic approaches to neural networks - the first one based on the mixtures of product components and the second one using the mixtures of dependence-tree distributions. The product mixture models can be efficiently estimated from data by means of EM algorithm and have some practically important properties. However, in some cases the simplicity of product components could appear too restrictive and a natural idea is to use a more complex mixture of dependence-tree distributions. By considering the concept of dependence tree we can explicitly describe the statistical relationships between pairs of variables at the level of individual components and therefore the approximation power of the resulting mixture may essentially increase. Nonetheless, in application to classification of numerals we have found that both models perform comparably and the contribution of the dependence-tree structures decreases in the course of EM iterations. Thus the optimal estimate of the dependence-tree mixture tends to converge to a simple product mixture model. We compare two probabilistic approaches to neural networks - the first one based on the mixtures of product components and the second one using the mixtures of dependence-tree distributions. The product mixture models can be efficiently estimated from data by means of EM algorithm and have some practically important properties. However, in some cases the simplicity of product components could appear too restrictive and a natural idea is to use a more complex mixture of dependence-tree distributions. By considering the concept of dependence tree we can explicitly describe the statistical relationships between pairs of variables at the level of individual components and therefore the approximation power of the resulting mixture may essentially increase. Nonetheless, in application to classification of numerals we have found that both models perform comparably and the contribution of the dependence-tree structures decreases in the course of EM iterations. Thus the optimal estimate of the dependence-tree mixture tends to converge to a simple product mixture model. (en)
Title	Pattern Recognition by Probabilistic Neural Networks - Mixtures of Product Components versus Mixtures of Dependence Trees Pattern Recognition by Probabilistic Neural Networks - Mixtures of Product Components versus Mixtures of Dependence Trees (en)
skos:prefLabel	Pattern Recognition by Probabilistic Neural Networks - Mixtures of Product Components versus Mixtures of Dependence Trees Pattern Recognition by Probabilistic Neural Networks - Mixtures of Product Components versus Mixtures of Dependence Trees (en)
skos:notation	RIV/67985556:_____/14:00434119!RIV15-GA0-67985556
http://linked.open...avai/riv/aktivita	I P
http://linked.open...avai/riv/aktivity	I, P(GA14-02652S), P(GAP403/12/1557)
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Grim, Jiří
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Ústav teorie informace a automatizace AV ČR, v. v. i.
http://linked.open...dnocenehoVysledku	35938
http://linked.open...ai/riv/idVysledku	RIV/67985556:_____/14:00434119
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Probabilistic Neural Networks; Product Mixtures; Mixtures of Dependence Trees; EM Algorithm (en)
http://linked.open.../riv/klicoveSlovo	EM Algorithm Mixtures of Dependence Trees Product Mixtures Probabilistic Neural Networks
http://linked.open...ontrolniKodProRIV	[92DD4494CE15]
http://linked.open...v/mistoKonaniAkce	Rome
http://linked.open...i/riv/mistoVydani	Rome
http://linked.open...i/riv/nazevZdroje	NCTA2014 - International Conference on Neural Computation Theory and Applications
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...vavai/riv/projekt	Developing Methods for Identifying and Evaluating Factors That Critically Affect Corporate Performance. Advanced measurement of material appearance
http://linked.open...UplatneniVysledku	2014
http://linked.open...iv/tvurceVysledku	Grim, Jiří Pudil, P.
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2014-10-22 (xsd:date)
number of pages	11 (xsd:int)
http://purl.org/ne...btex#hasPublisher	SCITEPRESS
https://schema.org/isbn	978-989-758-054-3

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