1. A system comprising: a processor; a memory communicatively coupled to the processor; an individual data object store, communicatively coupled to the processor, configured to store a plurality of individual data objects each defining features of a respective individual; a prediction set store, communicatively coupled to the processor, configured to store a plurality of prediction sets; and a prediction module, communicatively coupled to the memory, configured to: identify an individual having a plurality of first features; generate an individual data object comprising data specifying the first features; store the individual data object in the individual data object store; for each first feature among the plurality of first features, determine a respective probability distribution indicating, for each of a respective second feature among a plurality of second features, a probability that a person having the respective second feature has the first feature, thereby generating a plurality of probability distributions; use a probabilistic classifier to generate a merged probability distribution based on the plurality of probability distributions; use a Monte Carlo method to generate a prediction set based on the merged probability distribution, the prediction set including a plurality of prediction values for the individual, each respective prediction value being associated with one of the plurality of second features; and store the prediction set in the prediction set store.