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Memorias de investigación
Ponencias en congresos:
Learning multi-dimensional Bayesian network classifiers using Markov blankets: A case study in the prediction of HIV protease inhibitors
Año:2011
Áreas de investigación
  • Inteligencia artificial
Datos
Descripción
Multi-dimensional Bayesian network classifiers (MBCs) are Bayesian network classifiers especially designed to solve multidimensional classification problems, where each instance in the data set has to be assigned to one or more class variables. In this paper, we introduce a new method for learning MBCs from data basically based on determining the Markov blanket around each class variable using the HITON algorithm. Our method is applied to the human immunodeficiency virus (HIV) protease inhibitor prediction problem. The experimental study showed promising results in terms of classification accuracy, and we gained insight from the learned MBC structure into the different possible interactions among protease inhibitors and resistance mutations.
Internacional
Si
Nombre congreso
13th Conference on Artificial Intelligence in Medicine (AIME?11)
Tipo de participación
960
Lugar del congreso
Bled, Slovenia
Revisores
Si
ISBN o ISSN
DOI
Fecha inicio congreso
02/07/2011
Fecha fin congreso
Desde la página
29
Hasta la página
40
Título de las actas
Proceedings of Probabilistic Problem Solving in BioMedicine Workshop at 13th Conference on Artificial Intelligence in Medicine (AIME?11)
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Hanen Borchani (UPM)
  • Autor: Pedro Maria Larrañaga Mugica (UPM)
  • Autor: Maria Concepcion Bielza Lozoya (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: COMPUTATIONAL INTELLIGENCE GROUP
  • Departamento: Inteligencia Artificial
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