Journal
PATTERN RECOGNITION LETTERS
Volume 28, Issue 12, Pages 1438-1444Publisher
ELSEVIER
DOI: 10.1016/j.patrec.2007.02.014
Keywords
feature selection; matlab; machine learning; classification; challenge; benchmark; curriculum
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We used the datasets of the NIPS 2003 challenge on feature selection as part of the practical work of an undergraduate course on feature extraction. The students were provided with a toolkit implemented in Matlab. Part of the course requirements was that they should outperform given baseline methods. The results were beyond expectations: the student matched or exceeded the performance of the best challenge entries and achieved very effective feature selection with simple methods. We make available to the community the results of this experiment and the corresponding teaching material [Anon. Feature extraction course, ETH WS 2005/2006. http:// clopinet.com/isabelle/Projects/ETH]. These results also provide a new baseline for researchers in feature selection. (c) 2007 Elsevier B.V. All rights reserved.
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