MML Bayesian Nets with Decision Trees


Below is a list of publications pertaining to Minimum Message Length (MML) Bayesian networks and Bayesian belief networks - incorporating decision trees in their internal nodes.


[See also Ray Solomonoff (1926-2009) 85th memorial conference (Wedn 30 Nov - Fri 2 Dec 2011), 1st Call for Papers.]


Publications:
[The papers below are requestable in printed hard copy from either [more reliable] writing a letter to my ``snail mail'' postal address {see my home page, http://www.csse.monash.edu.au/~dld} or [perhaps less reliable] e-mail to enquiries At cs.monash.edu.au (if you send your name and postal address and make it clear what you want).]

D L Dowe and C S Wallace (1998). Kolmogorov complexity, minimum message length and inverse learning, abstract, page 144, 14th Australian Statistical Conference (ASC-14), Gold Coast, Qld, 6 - 10 July 1998.

Wallace, C.S. and D L Dowe (1999a). Minimum Message Length and Kolmogorov Complexity, Computer Journal (special issue on Kolmogorov complexity), Vol. 42, No. 4, pp270-283 - http://comjnl.oxfordjournals.org/cgi/reprint/42/4/270 and abstract.
[** This article is the Computer Journal's most downloaded ``full text as .pdf''. See, e.g., the Computer Journal, Editorial, vol. 48, no. 4 (2005), p381 (http://comjnl.oxfordjournals.org/cgi/reprint/48/4/381). **
And this is also Chris Wallace's most cited work which is co-authored by a still active MML researcher.]


Comley, Joshua W. and D L Dowe (2003). General Bayesian Networks and Asymmetric Languages, Proc. 2nd Hawaii International Conference on Statistics and Related Fields, 5-8 June, 2003.
%
% This and Comley & Dowe (2005) are the first two papers which do MML Bayesian nets combining both discrete and continuous attributes.
%
% {This concerns all of Generalised Bayesian nets, MML Bayesian nets, and
% MML Bayesian networks (or Generalised Bayes nets, MML Bayes nets, and
% MML Bayes networks (or Minimum Message Length Bayes nets and
% Minimum Message Length Bayes networks) or even mixed Bayes nets or
% mixed Bayesian nets or mixed Bayesian nets or mixed Bayesian networks)
% (or Generalised graphical models or MML graphical models, or
% Generalised directed graphical models or MML directed graphical models,
% or even mixed graphical models or MML mixed graphical models, or
% mixed directed graphical models or MML mixed directed graphical models,
% or MML Bayesian belief nets, or MML Bayesian belief networks);
% *and* deals with a mix of both continuous and discrete variables
% (or a mix of both numeric and symbolic variables)
% (or a mix of both numerical and categorical variables).
% There are decision trees (possibly with their own internal nodes) in the nodes of these Bayes nets.}
http://www.csse.monash.edu.au/~dld/Publications/2003/Comley+Dowe03_HICS2003.ref http://www.csse.monash.edu.au/~dld/Publications/2003/Comley+Dowe03_HICS2003_GeneralBayesianNetworksAsymmetricLanguages.pdf http://www.hicstatistics.org/2003StatsProceedings/Joshua Comley.pdf


P. J. Tan and D. L. Dowe (2004). MML Inference of Oblique Decision Trees, Proc. 17th Australian Joint Conference on Artificial Intelligence (AI'04), Cairns, Qld., Australia, Dec. 2004, Lecture Notes in Artificial Intelligence (LNAI) 3339, Springer-Verlag, pp1082-1088. http://www.csse.monash.edu.au/~dld/Publications/2004/Tan+Dowe2004.ref www.csse.monash.edu.au/~dld/Publications/2004/Tan+DoweAI2004.ps www.csse.monash.edu.au/~dld/Publications/2004/Tan+DoweAI2004.pdf
and www.csse.monash.edu.au/~ptan/tmp/posterpdf.pdf (and www.csse.monash.edu.au/~dld/Publications/2004/PTanObliqueDecisionTreePresentation.pdf).


Comley, Joshua W. and D L Dowe (2005). Minimum Message Length and Generalized Bayesian Net with Asymmetric Languages, Chapter 11 (pp265-294) in P. Gru:nwald, I. J. Myung and M. A. Pitt (eds.), Advances in Minimum Description Length: Theory and Applications, M.I.T. Press (MIT Press), April 2005, ISBN 0-262-07262-9. [Final camera ready copy was submitted in October 2003.] pp265-284 and pp285-294; p265, p266, p267, p268, p269, p270, p271, p272, p273, p274, p275, p276, p277, p278, p279, p280, p281, p282, p283, p284, p285, p286, p287, p288, p289, p290, p291, p292, p293, p294
[The paper was originally submitted with the title: ``Minimum Message Length, MDL and Generalised Bayesian Networks with Asymmetric Languages'', but this was (unfortunately?) changed to ``Minimum Message Length and Generalized Bayesian Nets with Asymmetric Languages'']
http://mitpress.mit.edu/catalog/item/default.asp?sid=4C100C6F-2255-40FF-A2ED-02FC49FEBE7C&ttype=2&tid=10478 Table of contents is at www.mitpress.mit.edu/catalog/item/default.asp?sid=C89E957F-2B61-42E0-9438-842E83E534BF&ttype=2&tid=10478&mode=toc
%
% This and Comley & Dowe (2003) are the first two papers which do MML Bayesian nets combining both discrete and continuous attributes.
%
% {This concerns all of Generalised Bayesian nets, MML Bayesian nets, and
% MML Bayesian networks (or Generalised Bayes nets, MML Bayes nets, and
% MML Bayes net, MML Bayes networks (or Minimum Message Length Bayes nets
% and Minimum Message Length Bayes networks) or even mixed Bayes nets or
% mixed Bayesian nets or mixed Bayesian nets or mixed Bayesian networks)
% (or Generalised graphical models or MML graphical models, or
% Generalised directed graphical models or MML directed graphical models,
% or even mixed graphical models or MML mixed graphical models, or
% mixed directed graphical models or MML mixed directed graphical models,
% or MML Bayesian belief nets, or MML Bayesian belief networks);
% *and* deals with a mix of both continuous and discrete variables
% (or a mix of both numeric and symbolic variables)
% (or a mix of both numerical and categorical variables).
% There are decision trees in the internal nodes of these Bayesian nets.}


Book: Wallace, C.S. (2005) [posthumous], Statistical and Inductive Inference by Minimum Message Length, Springer (Series: Information Science and Statistics), 2005, XVI, 432 pp., 22 illus., Hardcover, ISBN: 0-387-23795-X. (Link to table of contents, chapter headings and more.)

D. L. Dowe (2008a), "Foreword re C. S. Wallace", Computer Journal, Vol. 51, No. 5 (Sept. 2008) [Christopher Stewart WALLACE (1933-2004) memorial special issue [and front cover and back cover]], pp523-560 (and here). www.doi.org: 10.1093/comjnl/bxm117.

D. L. Dowe (2011 [was 2010]), "MML, hybrid Bayesian network graphical models, statistical consistency, invariance and uniqueness", Handbook of the Philosophy of Science - (HPS Volume 7) Philosophy of Statistics, Elsevier [ISBN: 978-0-444-51862-0 {ISBN 10: 0-444-51542-9 / ISBN 13: 978-0-444-51862-0}], pp901-982.

G. Visser, P. E. R. Dale, D. L. Dowe, E. Ndoen, M. B. Dale and N. Sipe (2012), "A novel approach for modeling malaria incidence using complex categorical household data: The minimum message length (MML) method applied to Indonesian data", Computational Ecology and Software, 2012, 2(3):140-159 (and Abstract). Published online 5 September 2012, www.IAEES.org .



  • Links to (links to) some of David Dowe's publications from some of the following years: 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011.



    Other links - links to pages on:
  • Minimum message length (MML),
  • Chris Wallace (1933-2004) (developer of MML in 1968),
  • "Bayes Not Bust! Why Simplicity is no problem for Bayesians",
  • Bayesianism, compression and intelligence [Dowe & Hajek (1997, 1998), Sanghi & Dowe (2003), Hernandez-Orallo & Dowe (2010)],
  • clustering and mixture modelling,
  • comparisons between MML and the subsequent Minimum Description Length (MDL) principle,
  • data: Bayesian Network (Repository) data sets (or Bayes Net data sets) (started by Nir Friedman), Bayesian networks and Related sites; and other data repositories,
  • Decision Trees using Minimum message length (MML),
  • Occam's razor (Ockham's razor),
  • Snob (program for MML clustering and mixture modelling),
  • (econometric) time series using MML,
  • medical research,
  • a probabilistic sports prediction competition (and further reading on probabilistic scoring),
  • red bayesiana, redes bayesianas, MML red bayesiana, MML redes bayesianas,
  • chess and game theory research,
  • do-goody stuff and saving the planet.

  • This page, http://www.csse.monash.edu.au/~dld/MMLBayesNet.html, was last updated no earlier than 2005.

    Copyright David L. Dowe, Monash University, Australia, 2005, etc.
    Copying is not permitted without expressed permission from David L. Dowe. This WWW page is http://www.cs.monash.edu.au/~dld/MMLBayesNet.html , and was last updated no earlier than Wed 2nd Nov 2005. E-mail David Dowe, d l d at cs.monash dot edu.au, for more information. WWW (URL): http://www.cs.monash.edu.au/~dld/ . Copyright Dr David L. Dowe, School of Computer Science and Softw. Engineering, Monash University, Clayton, Vic. 3168, Australia; 2 Nov 2005, etc.