1. A computer-implemented method comprising: receiving initial training data, the initial training data comprising initial training records, each initial training record identifying input data as input and a category as output; generating a trained predictive model using a first subset of the initial training data and a training function; generating intermediate training records including inputting input data of a second subset of the initial training records to the trained predictive model, each intermediate training record having a score; and generating a score normalization model using a score normalization training function and the intermediate training records.
1. A computer-implemented method comprising: receiving initial training data, the initial training data comprising initial training records, each initial training record identifying input data as input and a category as output; generating a trained predictive model using a first subset of the initial training data and a training function; generating intermediate training records including inputting input data of a second subset of the initial training records to the trained predictive model, each intermediate training record having a score; and generating a score normalization model using a score normalization training function and the intermediate training records. 9. The method of claim 1 , wherein each of the intermediate training records comprises a value for each distinct category in the initial training data.