Detection of elementary particles with the WiSARD n-tuple classifier

This work presents a weightless neural network model that learns multiple elementary particle collision phenomena. Having the AT- LAS Higgs Boson Machine Learning Challenge as the target dataset, a couple of abstractions were developed in order to achieve a fast and simple algorithm that would otherwise require much more sophisticated tools. Experimental results over the Higgs Boson ?-? decay and the B+ meson decay shows that the WiSARD n-tuple classifier provide a generic and lightweight method for studying a broad range of particle decay modes.