Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a recommendation engine. One of the methods includes receiving, from a plurality of data sources, input data; generating, using each of two or more propensity models, output data by providing training data from the input data to the respective propensity model; determining, for each of the propensity models, a first accuracy of the respective propensity model using the respective output data; determining, for each of the two or more propensity models, a second accuracy of the respective propensity model using testing data from the input data; selecting, using the first accuracies and the second accuracies for the two or more propensity models, a propensity model from the two or more propensity models; and providing, to a system, the selected propensity model to enable the system to generate a recommendation using the selected propensity model.