1. A computer implemented method comprising: receiving a first synthetic event, wherein the first synthetic event is derived from a first cohort comprising a first set of data and a second cohort comprising a second set of data, wherein the first synthetic event comprises a third set of data representing a result of a mathematical computation defined by the operation S(p1)==>F(p2), wherein S comprises a set of input facts with probability p1, wherein the set of input facts comprise the first cohort and the second cohort, wherein F comprises an inferred event with probability p2, wherein the term “event” means a particular set of data that represents, encodes, or records at least one of a thing or happening, and wherein each of the first set of data, the second set of data, the first cohort, the second cohort, the first synthetic event, and subcomponents thereof all comprise different events; creating a first rule set, wherein the first synthetic event is expected as a result of application of the first rule set to the first cohort and the second cohort; applying the first rule set to the first cohort and the second cohort, wherein a first result is achieved, and wherein the first result comprises a second event; comparing the second event to the first synthetic event, wherein a comparison is formed, the comparison comprising additional data that can be used to describe a difference between the second event and the first synthetic event; and storing the comparison.
8. The computer implemented method of claim 1 wherein creating the first rule set is accomplished by using a neural network to suggest rules that will allow creation of the first synthetic event from the first cohort and the second cohort.