: The paper proposes a different approach to data modeling. Analogous to the rejection method, where the misclassifications are removed and manually evaluated, we focus here on dif...
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
The knowledge discovery process encounters the difficulties to analyze large amount of data. Indeed, some theoretical problems related to high dimensional spaces then appear and de...
A linear programming technique is introduced that jointly performs feature selection and classifier training so that a subset of features is optimally selected together with the c...
When correct priors are known, Bayesian algorithms give optimal decisions, and accurate confidence values for predictions can be obtained. If the prior is incorrect however, these...
Thomas Melluish, Craig Saunders, Ilia Nouretdinov,...