Patent ID: 6640215
Filing Date: 2003-10-28
Classification: G06Q

Abstract:
A method of training models to maximize output variable modeling results within a specific interval, comprising:providing a target list from a modeling database; selecting a model type; choosing bounds for the specific interval; setting initial weight vectors Wi for the chosen model type; starting a first iteration by using the initial weight vectors Wi to calculate output variable classification scores gi for each target from the target list; sorting the list by output variable classification score; calculating an integral criterion of lift over the range of the specific interval; calculating a gradient criterion using the formula: Err=&Sum;â€ƒ&it;ln&af;(1+gi)-&Sum;i&epsi;resp&it;â€ƒ&it;ln&af;(gi),â€ƒcalculating gradient and non-gradient components of the full error; checking the full error for convergence below a tolerance level &egr;; finalizing a new model when convergence occurs; and calculating new weight vectors Wnew and beginning another iteration by using the new weight vectors to recalculate output variable classification scores for each target from the target list.