Data processing: financial – business practice – management – or co – Automated electrical financial or business practice or... – Finance
Reexamination Certificate
2006-02-21
2006-02-21
Patel, Jagdish N (Department: 3624)
Data processing: financial, business practice, management, or co
Automated electrical financial or business practice or...
Finance
C705S035000, C705S037000
Reexamination Certificate
active
07003490
ABSTRACT:
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.
REFERENCES:
patent: 5671279 (1997-09-01), Elgamal
patent: 5710887 (1998-01-01), Chelliah et al.
patent: 5712984 (1998-01-01), Hammond et al.
patent: 5737440 (1998-04-01), Kunkler
patent: 5740271 (1998-04-01), Kunkler et al.
patent: 5812668 (1998-09-01), Weber
patent: 5850446 (1998-12-01), Berger et al.
patent: 5889863 (1999-03-01), Weber
patent: 5898919 (1999-04-01), Yuen
patent: 5917931 (1999-06-01), Kunkler
patent: 5931917 (1999-08-01), Nguyen et al.
patent: 5940815 (1999-08-01), Maeda et al.
patent: 5943424 (1999-08-01), Berger et al.
patent: 5978840 (1999-11-01), Nguyen et al.
patent: 5983208 (1999-11-01), Haller et al.
patent: 5987132 (1999-11-01), Rowney
patent: 5987623 (1999-11-01), Ushida
patent: 5996076 (1999-11-01), Rowney et al.
patent: 6002767 (1999-12-01), Kramer
patent: 6014454 (2000-01-01), Kunkler
patent: 6016255 (2000-01-01), Bolan et al.
patent: 6026364 (2000-02-01), Whitworth
patent: 6026379 (2000-02-01), Haller et al.
patent: WO 99/03052 (1999-01-01), None
Mark Robert Segal, “Tree-Structured Methods for Longitudinal Data,” Jun. 1992, vol. 87, No. 418, Theory and Methods,Journal of the American Statistical Association.
Yan Yu and Diane Lambert, “Fitting Trees to Functional Data, With an Application to Time of Day Patterns,” 1999, unpublished manuscript, (http://www.stat.cornell.edu/Homepages/yyu/index.html), Cornell University.
Heping Zhang, “Classification Trees for Multiple Binary Responses,” Mar. 1998, vol. 93, No. 441, Theory and Methods,Journal of the American Statistical Association.
Tim K. Keyes and Martin S. Levy, “Goodness of Prediction Fit for Multivariate Linear Models,” Mar. 1996, vol. 91, No. 433, Theory and Methods,Journal of the American Statistical Association.
S. Kullback and R. A. Leibler, “On Information And Sufficiency,” 1951,Annals of Mathematical Statistics, 22, 79-86.
B. Forouraghi, L.W. Schmerr and G. M.Prabhu, “Fuzzy Multiobjective Optimization with Multivariate Regression Trees,” 1994, pp. 1400-1405,The Third IEEE International Conference on Fuzzy systems.
Leo Breiman, “Bagging Predictors,” 1996, pp. 123-140,Machine Learning, vol. 24, No. 2.
L. Breiman, J.H. Friedman, R.A. Olshen and C.J. Stone (1984),Classification and Regression Trees, Chapters 1, 2, 3, 8 and 11, Wadsworth, Belmont, CA.
S.F. Arnold,The Theory of Linear Models and Multivariate Analysis, 1981, Chapters 3, 17, 18, and 19, John Wiley & Sons, New York.
M.J.A. Berry, and G. Linoff,Mastering Data Mining the Art and Science of Customer Relationship Management, 1977, Chapters 1, 5 and 7, John Wiley Sons, Inc., New York.
Armstrong Teasdale LLP
GE Capital Commercial Finance, Inc.
Patel Jagdish N
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