Adil Omari (Computer Science Dept. at Universidad Autonoma de Madrid) Juan Jose Choquehuanca-Zevallos Roberto Dıaz-Morales
Machine learning algorithms have offered solutions to a wide range of problems, and some of the tasks found in the high energy physics field are one of them. However, given the nature of problems that are being faced in this field, machine estimates have to meet certain conditions (for instance, the Cramer-von Mises and Kolmogorov-Smirnov tests). Even more, when ensemble of classifiers is used as a solution for the given task, those conditions could be difficult to accomplish. In this talk, I will present a combination method for different output distributions and their use in the "Flavours of Physic" Challenge.