Mensaje de error

  • Unable to create CTools CSS cache directory. Check the permissions on your files directory.
  • Unable to create CTools CSS cache directory. Check the permissions on your files directory.
  • El archivo especificado temporary://filencaIdJ no se pudo copiar, porque el directorio de destino no está configurado correctamente. La causa puede ser un problema de permisos en el directorio o los archivos. Hay más información disponible en el registro del sistema.

Efficient Markov network structure discovery using independence tests

TítuloEfficient Markov network structure discovery using independence tests
Publication TypeConference Proceedings
Year of Conference2006
AuthorsBromberg F, Margaritis D, Honavar V
Conference NameProceedings of the SIAM Conference in Data Mining
Pagination141--152
Conference LocationBethesda, Maryland, USA
ISBN Number978-0-89871-611-5
Abstract

We present two algorithms for learning the structure of a Markov network from discrete data: GSMN and GSIMN. Both algorithms use statistical conditional independence tests on data to infer the structure by successively constraining the set of structures consistent with the results of these tests. GSMN is a natural adaptation of the Grow-Shrink algorithm of Margaritis and Thrun for learning the structure of Bayesian networks. GSIMN extends GSMN by additionally exploiting Pearl's well-known properties of conditional independence relations to infer novel independencies from known independencies, thus avoiding the need to perform these tests. Experiments on artificial and real data sets show GSIMN can yield savings of up to 70% with respect to GSMN, while generating a Markov network with comparable or in several cases considerably improved quality. In addition to GSMN, we also compare GSIMN to a forward-chaining implementation, called GSIMN-FCH, that produces all possible conditional independence results by repeatedly applying Pearl's theorems on the known conditional independence tests. The results of this comparison show that GSIMN is nearly optimal in terms of the number of tests it can infer, under a fixed ordering of the tests performed.

URLhttp://epubs.siam.org/doi/abs/10.1137/1.9781611972764.13
DOI10.1137-1.9781611972764.13
Texto completo: 
Miembros del DHARMa que son autores:: 
Peer reviewed?: 
1
Internacional?: 
1