DELVE

[Carl Edward Rasmussen]

                Announcing the release of DELVE

   DELVE --- Data for Evaluating Learning in Valid Experiments

DELVE contains a collection of datasets for use in evaluating the
predictive performance of empirical learning methods, such as linear
models, neural networks, smoothing splines, decision trees, and many
other regression and classification procedures.  DELVE also includes
software that facilitates using this data to assess learning methods
in a statistically valid way.  Ultimately, DELVE will include results
of applying many methods to many tasks, making comparisons between
methods much easier than in the past.

A preliminary version of DELVE is now freely available on the web at
URL http://www.cs.utoronto.ca/~delve.  From this web site, you can get
to the manual, the software for the DELVE environment, the DELVE
datasets, and precise definitions, source code, and results for
various learning methods.  Contributions of data and methods from
other researchers will be added to the web site in future.

DELVE was created at the university of Toronto by

  C. E. Rasmussen   R. M. Neal      G. E. Hinton   D. van Camp 
  M. Revow          Z. Ghahramani   R. Kustra      R. Tibshirani

--
                                                                 \
Carl Edward Rasmussen       Email: carl at cs.toronto.edu          o/\_
Dept of Computer Science    Phone: +1 (416) 978 7391            <|__,\
University of Toronto,      Home : +1 (416) 531 5685             ">   |
Toronto, ONTARIO,           FAX  : +1 (416) 978 1455              `   |
Canada, M5S 1A4             web  : http://www.cs.toronto.edu/~carl