Learning Bayesian Networks is NP-Complete. Chickering, D. M. In , pages 121-130. Springer New York, New York, NY, 1996. abstract bibtex Abstract Algorithms for learning Bayesian networks from data have two components: a scoring metric and a search procedure. The scoring metric computes a score reflecting the goodness-of-fit of the structure to the data. The search procedure tries to identify network.
@Incollection{Chickering1996,
author = {Chickering, David Maxwell},
title = {Learning Bayesian Networks is NP-Complete},
booktitle = {},
editor = {},
publisher = {Springer New York},
address = {New York, NY},
pages = {121-130},
year = {1996},
abstract = {Abstract Algorithms for learning Bayesian networks from data have two components: a scoring metric and a search procedure. The scoring metric computes a score reflecting the goodness-of-fit of the structure to the data. The search procedure tries to identify network.},
keywords = {}}
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