new tech report

[tibs@utstat.toronto.edu]

		    Classification by  pairwise coupling

                            Trevor Hastie
                           Stanford University

                            Robert Tibshirani
                           University of Toronto

We discuss a strategy for polychotomous classification that involves
estimating probabilities for each pair of classes and then coupling the
estimates together. The coupling model is similar to the Bradley-Terry
method for paired comparisons. We study the nature of the class
probability estimates that arise, and examine the performance of the
procedure in real and simulated datasets.  Classifiers used include
linear discriminants, nearest neighbours, and the support vector
machine.

Available at 

http://utstat.toronto.edu/tibs/research.html
ftp://utstat.toronto.edu/pub/tibs/coupling.ps

Comments welcome!
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Rob Tibshirani, Dept of Preventive Med & Biostats, and Dept of Statistics
Univ of Toronto, Toronto, Canada M5S 1A8.
Phone: 416-978-4642 (PMB), 416-978-0673 (stats). FAX: 416 978-8299
computer fax  416-978-1525 (please call or email me to inform)
tibs at utstat.toronto.edu. ftp: //utstat.toronto.edu/pub/tibs
http://www.utstat.toronto.edu/~tibs
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