Competitive baseline methods set new standards for the NIPS 2003 feature selection benchmark
        Isabelle Guyon, Jiwen Li, Theodor Mader, Patrick A. Pletscher, Georg Schneider and Markus Uhr
        Pattern Recognition Letters (in press)

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
. These results also provide a new baseline for researchers in feature selection.