Feature selection is fundamental to knowledge discovery from massive amount of high-dimensional data. In an effort to establish theoretical justification for feature selection al...
Abstract. This paper is concerned with the reliable inference of optimal treeapproximations to the dependency structure of an unknown distribution generating data. The traditional ...
Suppose that the only available information in a multi-class problem are expert estimates of the conditional probabilities of occurrence for a set of binary features. The aim is t...
Ludmila I. Kuncheva, Christopher J. Whitaker, Pete...
This paper proposes a method for dealing with numerical attributes in inductive concept learning systems based on genetic algorithms. The method uses constraints for restricting th...
— In this paper we propose PARINET, a new access method to efficiently retrieve the trajectories of objects moving in networks. The structure of PARINET is based on a combination...
Iulian Sandu Popa, Karine Zeitouni, Vincent Oria, ...