How Good Is Crude MDL for Solving the Bias-Variance Dilemma? An Empirical Investigation Based on Bayesian Networks

The bias-variance dilemma is a well-known and important problem in Machine Learning. It basically relates the generalization capability (goodness of fit) of a learning method to its corresponding complexity. When we have enough data at hand, it is possible to use these data in such a way so as to mi...

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Detalles Bibliográficos
Autores principales: Cruz-Ramírez, Nicandro, Acosta-Mesa, Héctor Gabriel, Mezura-Montes, Efrén, Guerra-Hernández, Alejandro, Hoyos-Rivera, Guillermo de Jesús, Barrientos-Martínez, Rocío Erandi, Gutiérrez-Fragoso, Karina, Nava-Fernández, Luis Alonso, González-Gaspar, Patricia, Novoa-del-Toro, Elva María, Aguilera-Rueda, Vicente Josué, Ameca-Alducin, María Yaneli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3966834/
https://www.ncbi.nlm.nih.gov/pubmed/24671204
http://dx.doi.org/10.1371/journal.pone.0092866

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3966834/
https://www.ncbi.nlm.nih.gov/pubmed/24671204
http://dx.doi.org/10.1371/journal.pone.0092866

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