Methods and system for predicting multi-variable outcomes

Abstract

Systems methods and recordable media for predicting multi-variable outcomes based on multi-variable inputs. Additionally, the models described can be used to predict the multi-variable inputs themselves, based on the multi-variable inputs, providing a smoothing function, acting as a noise filter. Both multi-variable inputs and multi-variable outputs may be simultaneously predicted, based upon the multi-variable inputs. The models find a critical subset of data points, or “tent poles” to optimally model all outcome variables simultaneously to leverage communalities among outcomes.

1 - 26 . (canceled)  
   
   
       27 . A method of generating a predictor model for predicting multivariable outcomes (a matrix of rows of Y-profiles) based upon multivariable inputs (a matrix of rows of X-profiles) with consideration of nuisance variables, said method comprising the steps of: 
 analyzing each X-profile row of multivariable inputs as an object;    calculating similarity among the objects;    selecting tent poles determined to be critical profiles in supporting a prediction function for predicting the Y-profiles;    optimizing the number of tent poles to minimize the error between the X-profiles and the Y-profiles; and    performing at least one of storing and outputting a prediction function for predicting the Y-profiles that results from said analyzing, calculating, selecting and optimizing wherein said Y-profiles are calculatable for continuous variables, logistic variables and ordinal variables.    
   
   
       28 - 35 . (canceled)