Bootstrapping nonparametric feature selection algorithms for mining small data sets
Jen-Lun Yuan · 2003
This paper presents feature selection algorithms based on nonparametric feature ranking indices, and demonstrates for small data sets that by bootstrapping feature ranking indices one uniformly (over various data sets and different ranking indices) improves the performance of correct detection of true features (i.e., probability of the top ranking features matching the true ones).