\begin{thebibliography}{28}
\providecommand{\natexlab}[1]{#1}
\providecommand{\url}[1]{\texttt{#1}}
\expandafter\ifx\csname urlstyle\endcsname\relax
  \providecommand{\doi}[1]{doi: #1}\else
  \providecommand{\doi}{doi: \begingroup \urlstyle{rm}\Url}\fi

\bibitem[Blake and Merz(1998)]{uci_database}
C. L. Blake and C. J. Merz.
\newblock {UCI} repository of machine learning databases, 1998.
\newblock URL \url{http://www.ics.uci.edu/$\sim$mlearn/MLRepository.html}.

\bibitem[Buntine(1991)]{Buntine2.UAI91}
W.~Buntine.
\newblock Theory refinement on {B}ayesian networks.
\newblock In \emph{Proceedings of the Seventh Annual Conference on Uncertainty
  in Artificial Intelligence (UAI--91)}, pages 52--60, San Mateo, California,
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\bibitem[Cerquides(2003)]{cerquides.phd}
Jes\'{u}s Cerquides.
\newblock \emph{Improving {B}ayesian network classifiers}.
\newblock PhD thesis, Technical University of Catalonia, 2003.

\bibitem[Cerquides and de~M\`{a}ntaras(2003)]{cerquides.icml03}
Jes\'{u}s Cerquides and L\'{o}pez de~M\`{a}ntaras.
\newblock Tractable {B}ayesian learning of tree augmented naive {B}ayes
  classifiers.
\newblock \emph{Proceedings of the Twentieth International Conference on
  Machine Learning (ICML 2000)}, pages 75--82, 2003.

\bibitem[Cooper and Herskovits(1992)]{cooper92}
Gregory~F. Cooper and Edward Herskovits.
\newblock A {B}ayesian method for the induction of probabilistic networks from
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\newblock \emph{Machine Learning}, 9\penalty0 (4):\penalty0 309--347, 1992.

\bibitem[Dash and Cooper(2002)]{dash02.icml}
Denver Dash and Gregory~F. Cooper.
\newblock Exact model averaging with naive {B}ayesian classifiers.
\newblock \emph{Proceedings of the Nineteenth International Conference on
  Machine Learning (ICML 2002)}, pages 91--98, January 2002.

\bibitem[Dash and Cooper(2003)]{dash03.aistats}
Denver Dash and Gregory~F. Cooper.
\newblock Exact model averaging with discrete {B}ayesian classifiers.
\newblock In C.~M. Bishop and B.~J. Frey, editors, \emph{Proceedings of the
  Ninth International Workshop on Artificial Intelligence and Statistics}, Key
  West, Florida, 2003.

\bibitem[Domingos(2000)]{domingos.icml00}
Pedro Domingos.
\newblock {B}ayesian averaging of classifiers and the overfitting problem.
\newblock \emph{Proceedings of the Seventeenth International Conference on
  Machine Learning (ICML 2000)}, pages 223--230, 2000.

\bibitem[Domingos and Pazzani(1997)]{domingos97}
Pedro Domingos and Michael Pazzani.
\newblock On the optimality of the simple {B}ayesian classifier under zero-one
  loss.
\newblock \emph{Machine Learning}, 29:\penalty0 103--130, 1997.

\bibitem[Druzdzel(1999)]{druzdzel99a}
Marek~J. Druzdzel.
\newblock {SMILE}: {S}tructural {M}odeling, {I}nference, and {L}earning
  {E}ngine and {GeNIe}: A development environment for graphical
  decision-theoretic models.
\newblock In \emph{Proceedings of the Sixteenth National Conference on
  Artificial Intelligence (AAAI--99)}, pages 902--903, Orlando, FL, July 18--22
  1999.

\bibitem[Duda and Hart(1973)]{duda73}
Richard~O. Duda and Peter~E. Hart.
\newblock \emph{Pattern Classification and Scene Analysis}.
\newblock John Wiley and Sons, New York, NY, 1973.

\bibitem[Egan(1975)]{egan75}
J. P. Egan.
\newblock \emph{Signal Detection Theory and ROC Analysis}.
\newblock Academic Press, New York, New York, 1975.

\bibitem[Friedman(1997)]{friedmanJerome97}
Jerome Friedman.
\newblock On bias, variance, 0/1--loss, and the curse-of-dimensionality.
\newblock \emph{Data Mining and Knowledge Discovery}, 1:\penalty0 55--77, 1997.

\bibitem[Friedman et~al.(1997)Friedman, Geiger, and
  Goldszmidt]{friedman97bayesianClassifiers}
Nir Friedman, Dan Geiger, and Moises Goldszmidt.
\newblock {B}ayesian network classifiers.
\newblock \emph{Machine Learning}, 29\penalty0 (2--3):\penalty0 131--163, 1997.

\bibitem[Friedman and Koller(2003)]{Friedman_ML2003}
Nir Friedman and Daphne Koller.
\newblock Being {B}ayesian about network structure. a {B}ayesian approach to
  structure discovery in {B}ayesian networks.
\newblock \emph{Machine Learning}, 50\penalty0 (1--2):\penalty0 95--125, 2003.

\bibitem[Heckerman et~al.(1995)Heckerman, Geiger, and Chickering]{heckerman95}
David Heckerman, Dan Geiger, and David~M. Chickering.
\newblock Learning {B}ayesian networks: The combination of knowledge and
  statistical data.
\newblock \emph{Machine Learning}, 20:\penalty0 197--243, 1995.

\bibitem[Kohavi and John(1997)]{kohavi97wrappers}
Ron Kohavi and George~H. John.
\newblock Wrappers for feature subset selection.
\newblock \emph{Artificial Intelligence}, 97\penalty0 (1-2):\penalty0 273--324,
  1997.
\newblock URL \url{citeseer.nj.nec.com/kohavi96wrappers.html}.

\bibitem[Langley and Sage(1994)]{Langley.UAI94}
Pat Langley and Stephanie Sage.
\newblock Induction of selective {B}ayesian classifiers.
\newblock In \emph{Proceedings of the Tenth Annual Conference on Uncertainty in
  Artificial Intelligence (UAI--94)}, pages 399--406, San Francisco, CA, 1994.
  Morgan Kaufmann Publishers.

\bibitem[Lauritzen and Spiegelhalter(1988)]{lauritzen88}
Steffen~L. Lauritzen and David~J. Spiegelhalter.
\newblock Local computations with probabilities on graphical structures and
  their application to expert systems.
\newblock \emph{Journal of the Royal Statistical Society, Series B
  (Methodological)}, 50\penalty0 (2):\penalty0 157--224, 1988.

\bibitem[Madigan and Raftery(1994)]{madigan94}
David Madigan and Adrian~E. Raftery.
\newblock Model selection and accounting for model uncertainty in graphical
  models using {O}ccam's window.
\newblock \emph{Journal of the American Statistical Association}, 89:\penalty0
  1535--1546, 1994.

\bibitem[Madigan and York(1995)]{madigan95b}
David Madigan and J.~York.
\newblock {B}ayesian graphical models for discrete data.
\newblock \emph{International Statistical Review}, 63:\penalty0 215--232, 1995.

\bibitem[Meila and Jaakkola(2000)]{Meila45.UAI-2000}
Marina Meila and Tommi~S. Jaakkola.
\newblock Tractable {B}ayesian learning of tree belief networks.
\newblock In \emph{Uncertainty in Artificial Intelligence: Proceedings of the
  Sixteenth Conference (UAI-2000)}, pages 380--388, San Francisco, CA, 2000.
  Morgan Kaufmann Publishers.

\bibitem[Moore and Lee(1998)]{moore-cached}
Andrew Moore and Mary~Soon Lee.
\newblock Cached sufficient statistics for efficient machine learning with
  large datasets.
\newblock \emph{Journal of Artificial Intelligence Research}, 8:\penalty0
  67--91, March 1998.

\bibitem[Ng and Jordan(2002)]{Ng.NIPS.02}
Andrew~Y. Ng and Michael~I. Jordan.
\newblock On discriminative vs. generative classifiers: A comparison of
  logistic regression and naive {B}ayes.
\newblock In T.~G. Dietterich, S.~Becker, and Z.~Ghahramani, editors,
  \emph{Advances in Neural Information Processing Systems 14}, pages 841--848,
  Cambridge, MA, 2002. MIT Press.

\bibitem[Pearl(1988)]{pearl88}
Judea Pearl.
\newblock \emph{Probabilistic Reasoning in Intelligent Systems: Networks of
  Plausible Inference}.
\newblock Morgan Kaufmann Publishers, Inc., San Mateo, CA, 1988.

\bibitem[Spirtes et~al.(1993)Spirtes, Glymour, and Scheines]{spirtes93}
Peter Spirtes, Clark Glymour, and Richard Scheines.
\newblock \emph{Causation, Prediction, and Search}.
\newblock Springer Verlag, New York, 1993.

\bibitem[Verma and Pearl(1991)]{Verma.UAI90}
T. S. Verma and Judea Pearl.
\newblock Equivalence and synthesis of causal models.
\newblock In P. P. Bonissone, M.~Henrion, L. N. Kanal, and J. F. Lemmer, editors,
  \emph{Uncertainty in Artificial Intelligence~6}, pages 255 --269. Elsevier
  Science Publishing Company, Inc., New York, N. Y., 1991.

\bibitem[Volinsky(1997)]{volinsky-phd-thesis}
C. T. Volinsky.
\newblock \emph{{B}ayesian Model Averaging for Censored Survival Models}.
\newblock {PhD} dissertation, University of Washington, 1997.

\end{thebibliography}
