MULTIVARIATE RESPONSES USING CLASSIFICATION AND REGRESSION TREES SYSTEMS AND METHODS

The present invention is a method of allowing inclusion of more than one variable in a Classification and Regression Tree (CART) analysis. The method includes predicting y using p exploratory variables, where y is a multivariate, continuous response vector, describing a probability density function...

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Bibliographic Details
Main Author KEYES, TIM, K
Format Patent
LanguageEnglish
French
Published 07.02.2002
Edition7
Subjects
CALCULATING
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Summary:The present invention is a method of allowing inclusion of more than one variable in a Classification and Regression Tree (CART) analysis. The method includes predicting y using p exploratory variables, where y is a multivariate, continuous response vector, describing a probability density function at "parent" and "child" nodes using a multivariate normal distribution, which is a function of y, and defining a split function where "child" node distributions are individualized, compared to the parent node. In one embodiment a system is configured to implement the multivariate CART analysis for predicting behavior in a non-performing loan portfolio.
Bibliography:Application Number: WO2001US21753