9786130335533 - variable-order bayesian network: bayesian network, graphical model, random variable, conditional independence, directed acyclic graph, variable-order markov model, markov chain, markov property (3 risultati)
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 34,00
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -High Quality Content by WIKIPEDIA articles! Variable-order Bayesian network models provide an important extension of both the Bayesian network models and the variable-order Markov models. Variable-order Bayesian network models are…used in machine learning in general and have shown great potential in bioinformatics applications. These models extend the widely-used position weight matrix models, Markov models, and Bayesian network models. In contrast to the BN models, where each random variable depends on a fixed subset of random variables, in Variable-order Bayesian network models these subsets may vary based on the specific realization of observed variables. The observed realizations are often called the context and, hence, Variable-order Bayesian network models are also known as context-specific Bayesian networks. The flexibility in the definition of conditioning subsets of variables turns out to be a real advantage in classification and analysis applications, as the statistical dependencies between random variables in a sequence of variables may be taken into account efficiently, and in a position-specific and context-specific manner. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 35,89
EUR 60,69 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! Variable-order Bayesian network models provide an important extension of both the Bayesian network models and the variable-order Markov models. Variable-order Bayesian network models are used…in machine learning in general and have shown great potential in bioinformatics applications. These models extend the widely-used position weight matrix models, Markov models, and Bayesian network models. In contrast to the BN models, where each random variable depends on a fixed subset of random variables, in Variable-order Bayesian network models these subsets may vary based on the specific realization of observed variables. The observed realizations are often called the context and, hence, Variable-order Bayesian network models are also known as context-specific Bayesian networks. The flexibility in the definition of conditioning subsets of variables turns out to be a real advantage in classification and analysis applications, as the statistical dependencies between random variables in a sequence of variables may be taken into account efficiently, and in a position-specific and context-specific manner.
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Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 109,85
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Variable-order Bayesian Network | Bayesian Network, Graphical Model, Random Variable, Conditional Independence, Directed Acyclic Graph, Variable-order Markov Model, Markov Chain, Markov Property | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786130335533 | Verantw…ortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.
