Feature set partitioning generalizes the task of feature selection by partitioning the feature set into subsets of features that are collectively useful, rather than by finding a ...
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...
– This paper presents an ongoing investigation to select optimal subset of features from set of well-known myoelectric signals (MES) features in time and frequency domains. Four ...
Learning algorithms, as NN or C4.5 require adequate sets of examples. In the paper we present the usability of genetic algorithms for selection significant features. Fitness of ind...
The purpose of this research is to develop effective machine learning or data mining techniques based on flexible neural tree FNT. Based on the pre-defined instruction/operator se...