The usability of mobile robots for surveillance, search and rescue missions can be significantly improved by intelligent functionalities decreasing the cognitive load on the opera...
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Boosting is a set of methods for the construction of classifier ensembles. The differential feature of these methods is that they allow to obtain a strong classifier from the comb...
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions c...