We report on an empirical comparison of several multivariate classification techniques (e.g., random forests, Bayesian classification, support vector machines) for signal identification; our experiments use K* mass as a test case. We show 1) the effect of using different cost matrices in generalization performance and 2) how information about physical constraints obtained from kinematic fitting...
