  We have carried out an exercise in the classification of W+W- and ttbar
events as produced in a high-energy proton-proton collider, motivated in part
by the current tension between the measured and predicted values of the WW
cross section. The performance of the random forest classifier surpasses that
of a standard cut-based analysis. Furthermore, the distortion of the
distributions of key kinematic event features is relatively slight, suggesting
that systematic uncertainties due to modeling might be reduced. Finally, our
random forest can tolerate missing features such as missing transverse energy
without a severe degradation of its performance.
