Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
A novel approach for comparing sequences of observations using an explicit-expansion kernel is demonstrated. The kernel is derived using the assumption of the independence of the ...
In this paper, we propose a new classification method that addresses classification in multiple categories of textual documents. We call it Matrix Regression (MR) due to its resem...
Iulian Sandu Popa, Karine Zeitouni, Georges Gardar...
— To obtain accurate modeling results, it is of primal importance to find optimal values for the hyperparameters in the Support Vector Regression (SVR) model. In general, we sea...