SANGE -Stochastic Automata Networks Generator. A tool to efficiently predict events through structured Markovian models extended versionReport as inadecuate




SANGE -Stochastic Automata Networks Generator. A tool to efficiently predict events through structured Markovian models extended version - Download this document for free, or read online. Document in PDF available to download.

1 PUCRS - Pontifícia Universidade Católica do Rio Grande do Sul Porto Alegre 2 Université Grenoble Alpes Saint Martin d-Hères 3 MESCAL - Middleware efficiently scalable Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d-Informatique de Grenoble

Abstract : The use of stochastic formalisms, such as Stochastic Automata Networks SAN, can be very useful for statistical prediction and behavior analysis.Once well fitted, such formalisms can generate probabilities about a target reality.These probabilities can be seen as a statistical approach of knowledge discovery.However, the building process of models for real world problems is time consuming even for experienced modelers.Furthermore, it is often necessary to be a domain specialist to create a model.This work illustrates a new method to automatically learn simple SAN models directly from a data source.This method is encapsulated in a tool called SAN GEnerator SANGE.Through examples we show how this new model fitting method is powerful and relatively easy to use; therefore this can grant access to a much broader community to such powerful modeling formalisms.

Keywords : Stochastic Automata Networks model fitting time series prediction





Author: Joaquim Assunção - Paulo Fernandes - Lucelene Lopes - Angelika Studeny - Jean-Marc Vincent -

Source: https://hal.archives-ouvertes.fr/



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