General Electric Company
PREDICTIVE FRAMEWORK FOR ADMISSION PASS VALUATION

Abstract:

The example embodiments are directed to a predictive framework configured to selectively implement a multi-layered predictive function for admission pass valuation. In one example, the method may include receiving an identification of an admission pass including event attributes and seat location attributes, executing a first predictive algorithm on the event attributes to generate a first predicted value for the admission pass based on values of historical admission passes, executing a second predictive algorithm on the seat location attributes to generate a second predicted value for the admission pass based on the historical values of the historical admission passes, refining the first predicted value based on the second predicted value to generate a multi-layered predicted value for the admission pass, and outputting a display of the multi-layered predicted value to a display.