Abstract: A method that includes (a) receiving a training dataset, a testing dataset, a number of iterations, and a parameter space of possible parameter values that define a base model, (b) for the number of iterations, performing a parametric search process that produces a report that includes information concerning a plurality of machine learning models, where the parametric search process includes (i) generating a Bayesian optimized parameter space with an option to validate through Stratified Kfold cross validation, where an optimized parameter set includes training data from the training dataset, and testing data from the testing dataset, (ii) running the base model with the final optimized parameter set, thus yielding model results for the plurality of machine learning models, (iii) calculating Kolmogorov-Smirnov (KS) statistics for the model results, and (iv) saving the model results and the KS statistics to the report, and (c) sending the report to a user device.