Artificial neural networks are widely spread models that outperform more basic, but
explainable machine learning models like classification decision tree. However, their lack of …

Currently knowledge management and discovery plays crucial role in different industries.
Apart from that in many cases decisions made by companies in mission critical areas (like …

Artificial neural networks (ANN) are widely used in machine learning. They are powerful non-
linear models that can be trained in a supervised, semi-supervised, and unsupervised …

The paper describes an algorithm for approximation of trained radial basis function neural
network (RBFNN) classification boundary with the help of elliptic rules. These rules can later …

This paper describes the application of the symbolic knowledge extraction approach to RBF
Neural Network (RBFNN). The proposed method retrieves a set of concise and interpretible …

Mākslīgie neironu tīkli (MNT) tiek plaši izmantoti mašīnmācībā. Tie ir jaudīgi nelineāri
modeļi, kurus var apmācīt uzraudzītā, daļēji uzraudzītā un neuzraudzītā veidā. Universāls …