In problems of prediction, as well as using "yes"/"no" predictions, we would
encourage people to consider also using probabilistic prediction, where the
score assigned to a probabilistic prediction is given according to the
(negative) logarithm of the stated probability of the event.
More on this is given in (e.g.)
D. L. Dowe, G. E. Farr, A. J. Hurst and K. L. Lentin (1996):
"Information-theoretic football tipping",
in N. de Mestre (ed.), 3rd Conference on Mathematics and Computers in Sport,
Bond University, Qld, Australia, 233-241, 1996 ; or
D. L. Dowe et al.,
Kullback-Leibler distance, probability and football prediction.
Scoring functions for probabilistic prediction
Scoring functions for
probabilistic prediction and
Gaussian prediction.
Australian football as an example of probabilistic prediction
Link to (new) Monash Computer Science Footy Tipping Page
(and how to join).
Link to K.L. Lentin's 1995 Footy Tipping Page, including (Probabilistic) Info Theory Tipping Results.
Link to A. J. Hurst's 1996 Footy TippingResults, including Probabilistic and Gaussian Results.
CSC423 Learning and Prediction (2nd semester, Comp. Sci. Hons. course)
If you are at or near Monash University and would like to know about the theory of probabilistic prediction or of MML,
you could attend my 1998 2nd semester
Comp. Sci.Hons. course
CSC423 Learning and Prediction,
starting on the week of Mon 20th July '98.
This page was put together by
Dr. David Dowe,
Dept. of Computer Science, Monash University, Clayton, Vic. 3168, Australia
e-mail:
dld@cs.monash.edu.au (Fax: +61 3 9905-5146)
(and was started on Mon 24th Mar. 1997) and was last updated no earlier than Fri 20th Jan. 1998.
Copyright
David L. Dowe,
Monash University, Australia,
24 Mar 1997, 20 Jan 1998, 7 May 1998, etc.
Copying is not permitted without expressed permission from
David L. Dowe.