How good is crude MDL for solving the bias-variance dilemma? An empirical investigation based on Bayesian networks.

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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Bibliographic Details
Main Authors: Nicandro Cruz-Ramírez, Héctor Gabriel Acosta-Mesa, Efrén Mezura-Montes, Alejandro Guerra-Hernández, Guillermo de Jesús Hoyos-Rivera, Rocío Erandi Barrientos-Martínez, Karina Gutiérrez-Fragoso, Luis Alonso Nava-Fernández, Patricia González-Gaspar, Elva María Novoa-del-Toro, Vicente Josué Aguilera-Rueda, María Yaneli Ameca-Alducin
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3966834?pdf=render

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http://europepmc.org/articles/PMC3966834?pdf=render

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