Métodos de inferencia estadística para entrenamiento de modelos ocultos de Markov

• Mendoza León, Ricardo Antonio ^[1]
  1. [1] Politécnico Grancolombiano

     Politécnico Grancolombiano

     Colombia

     
• Localización: Elementos, ISSN-e 2248-5252, Vol. 1, Nº. 1, 2011 (Ejemplar dedicado a: Elementos), págs. 57-70
• Idioma: español
• DOI: 10.15765/e.v1i1.191
• Enlaces
  • Texto completo (pdf)
• Resumen

  • Este documento presenta una revisión general de las diferentes aproximaciones y métodos en inferencia estadística, aplicados al problema de entrenamiento o ajuste de parámetros en Modelos Ocultos de Markov. Se tratarán los algoritmos EM (Expectation Maximization) y GEM (Generalized Expectation Maximization), el marco de modelos gráficos y sus algoritmos ML (Maximum Likelihood) y MAP (Maximum a Posteriori), así como modelos de conjunto, variacionales y métodos de muestreo MCMC (Markov Chain Montecarlo).

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