Sensitivity analysis is one of the most interesting and preoccupying areas in optimization. Many attempts are made to investigate the problem's behavior when the input data c...
In this paper, we propose a new method to perform the first derivative estimation of a discrete intensity distribution. This approach is based on a non-additive aggregation proce...
Florence Jacquey, Kevin Loquin, Frederic Comby, Ol...
Previous discretization techniques have discretized numeric attributes into disjoint intervals. We argue that this is neither necessary nor appropriate for naive-Bayes classifiers...
Discretization refers to splitting the range of continuous values into intervals so as to provide useful information about classes. This is usually done by minimizing a goodness m...
In real-life decision analysis, the probabilities and values of consequences are in general vague and imprecise. One way to model imprecise probabilities is to represent a probabi...