This paper proposes a novel approach for directly tuning the gaussian kernel matrix for one class learning. The popular gaussian kernel includes a free parameter, σ, that requires...
Paul F. Evangelista, Mark J. Embrechts, Boleslaw K...
Many statistical methods have been proposed to estimate causal models in classical situations with fewer variables than observations. However, modern datasets including gene expres...
This paper presents a new method for constructing ensembles of classifiers based on immune network theory, one of the most interesting paradigms within the field of artificial imm...
Currently statistical and artificial neural network methods dominate in financial data mining. Alternative relational (symbolic) data mining methods have shown their effectiveness...
Background: In the analysis of networks we frequently require the statistical significance of some network statistic, such as measures of similarity for the properties of interact...