1. A computer-implemented method, the method comprising: receiving a training data set that comprises a plurality of examples, wherein each example comprises one or more features and an answer; generating a plurality of modified training data sets, wherein generating each of the modified training data sets comprises applying a respective filter or combination of filters to examples in the training data set to generate the examples of the modified training data set, the filter or combination of filters altering one or more of the examples; training a plurality of predictive models, including training each of one or more predictive models using a different respective modified training data set of the plurality of modified training data sets; determining a respective accuracy for each of the plurality of predictive models; identifying a most accurate predictive model based on the determined respective accuracies; and specifying an association between the training data set and the filter or combination of filters used to generate the modified training data set that was used to train the most accurate predictive model.