Adaptive random trees integer non-linear programming

US8255423B2 · kind B2 · utility

Assignee

• Fair Isaac Corporation · US

Inventors

• Christopher Allan Ralph · Toronto, CA
• Michael S. Sossi · San Francisco, US
• Stefan Kuzminski · New York, US
• Helen Geraldine E. Rosario · Ellington, US
• Yaxin Liu · San Jose, US

Key dates

• Filing date: Apr 27, 2009
• Grant date: Aug 28, 2012
• Expiry date: May 24, 2029

Classification

• Technology area (CPC G): Physics
• CPC primary: G06Q10/10
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

Abstract

A system and method for building segmented scorecards for a population is presented. A model of the population is built using a model builder computer, and one or more variables used by the model builder to build the model is stored in a repository. A scorecard is generated for each segment of the population based on the model and using an adaptive random tree computer program. Next, the scorecard for each segment is enhanced using a integer non-linear programming computer program to determine optimal score weights associated with the variables used by the model builder to build the model, and to generate an enhanced segmented scorecard for the population.