Multivariate decision tree designing for the classification of multi-jet topologies in e+e− collisions

The binary decision tree method is used to separate between several multi-jet topologies in e+e− collisions. Instead of the univariate process usually taken, a new design procedure for constructing multivariate decision trees is proposed. The segmentation is obtained by considering some features functions, where linear and non-linear discriminant functions and a minimal distance method are used. The classification focuses on ALEPH simulated events, with multi-jet topologies. Compared to a standard univariate tree, the multivariate decision trees offer significantly better performance.