We have shown how we can characterize a chemical process via the combination of a kinetic model and entropic sampling. Unlike optimization methods, clustering high quality reveal multiple options to control the chemical process. Visualizing each cluster provides us about characteristics of each cluster, which are useful in choosing the best option. In our method, the accuracy gain over random sampling is obtained by approximating the long-tail distribution of e(x) by weighted samples. In visualizing two dimensional DoS as in Figure the other variable may also be long-tailed. In this case, it might be beneficial to apply two dimensional DoS estimation techniques. Our code for EPA is available at .