We investigate improvements of AdaBoost that can exploit the fact that the weak hypotheses are one-sided, i.e. either all its positive (or negative) predictions are correct. In pa...
Background: Recursive Feature Elimination is a common and well-studied method for reducing the number of attributes used for further analysis or development of prediction models. ...
In this work an improvement of an initial approach to design Artificial Neural Networks to forecast Time Series is tackled, and the automatic process to design Artificial Neural N...
Classification of texts potentially containing a complex and specific terminology requires the use of learning methods that do not rely on extensive feature engineering. In this w...
— This work shows comparatively the capacity of five Fuzzy Lattice Neurocomputing (FLN) classifiers. The mechanics of the five classifiers are illustrated geometrically on the pl...
Al Cripps, Vassilis G. Kaburlasos, Nghiep Nguyen, ...