Patent ID: 8165853
Filing Date: 2012-04-24
Classification: G06Q

Abstract:
1. A machine-based method comprising receiving historical multi-dimensional data representing multiple variables, transforming the variables into one or more predictive variables, including Bayesian renormalized variables, the transforming of the variables into the Bayesian renormalized variables comprising adjusting a response frequency associated with a variable by a Bayesian analysis based on a priori response frequency associated with the variable, and the adjusting of the response frequency associated with a variable comprising associating the variable with a weight to regress the response frequency toward a mean response frequency, adjusting a population of variables to represent interaction effects exhibited by the historical data, the population of variables being selected from the multiple variables for use in generating a predictive model, at least some of the multiple variables being excluded from the selected population of variables, the interaction effects including interactions of at least some excluded variables with each other and with variables in the selected population of variables, and using the adjusted population of variables that are transformed in generating the predictive model for use in interacting with a commercial system.