In recent years, the increasing interest in fuzzy rough set theory has allowed the definition of novel accurate methods for feature selection. Although their stand-alone applicati...
For supervised learning, feature selection algorithms attempt to maximise a given function of predictive accuracy. This function usually considers the ability of feature vectors t...
— One of the main obstacles facing the application of computational intelligence technologies in pattern recognition (and indeed in many other tasks) is that of dataset dimension...
Traditionally, membership to the fuzzy-rough lower, resp. upper approximation is determined by looking only at the worst, resp. best performing object. Consequently, when applied t...