By Topic

State-of-the-Art and Evolution in Public Data Sets and Competitions for System Identification, Time Series Prediction and Pattern Recognition

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Vandewalle, J. ; ESAT-SCD, Katholieke Univ. Leuven, Belgium ; Suykens, J. ; De Moor, B. ; Lendasse, A.

It is the aim of reproducible research to provide mechanisms for objective comparison of methods, algorithms, software and procedures in various research topics. In this paper, we discuss the role of data sets, benchmarks and competitions in the fields of system identification, time series prediction, classification, and pattern recognition in view of creating an environment of reproducible research. Important elements are the data sets, their origin, and the comparison measures that will be used to rank the performance of the methods. The issues are discussed, a comparison is made and recommendations are given.

Published in:

Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on  (Volume:4 )

Date of Conference:

15-20 April 2007