International Business Machines Corporation
Modeling a correlation and a causation link of hidden evidence

Abstract:

A method, system, and non-transitory compute readable medium for hidden evidence correlation and causation linking including a forecasting device configured to forecast hidden evidence found in relation to a user input in hidden cycle measurements into future forecasted cycle measurements, where the forecasted hidden cycles are transformed into an amplitude versus frequency histogram with each histogram being compared to each other histogram and determined if causation is a candidate, and if causation is a candidate, a probability density function is applied to produce a degree of causation of a causation link for the hidden evidence in relation to the user input.