Reference : Learning parameters in discrete naive Bayes models by computing fibers of the parametriz...

	Document type :	Scientific congresses and symposiums : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/2268/34058

Title :	Learning parameters in discrete naive Bayes models by computing fibers of the parametrization map
Language :	English
Author, co-author :	Auvray, Vincent [ > > ]
	Wehenkel, Louis [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Publication date :	20-Dec-2008
Main document title :	NIPS ´08 Workshop: Algebraic and combinatorial methods in machine learning
Audience :	International
Event name :	NIPS ´08 Workshop: Algebraic and combinatorial methods in machine learning
Keywords :	[en] Machine Learning ; Graphical Models
Abstract :	[en] Discrete Naive Bayes models are usually defined parametrically with a map from a parameter space to a probability distribution space. First, we present two families of algorithms that compute the set of parameters mapped to a given discrete Naive Bayes distribution satisfying certain technical assumptions. Using these results, we then present two families of parameter learning algorithms that operate by projecting the distribution of observed relative frequencies in a dataset onto the discrete Naive Bayes model considered. They have nice convergence properties, but their computational complexity grows very quickly with the number of hidden classes of the model.
Target :	Researchers ; Professionals ; Students
Permalink :	http://hdl.handle.net/2268/34058
Commentary :	Video lecture and slides available at http://videolectures.net/aml08_auvray_lpdnbmcfpm/

	File(s) associated to this reference
	Fulltext file(s): File Commentary Version Size Access Open access aml08_auvray_lpdnbmcfpm_01.pdf Author preprint 91.67 kB View/Open Additional material(s): File Commentary Version Size Access Open access g6y7gH-aml08_auvray_lpdnbmcfpm_01.pdf Presentation slides - 91.67 kB View/Open

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