Data processing: structural design – modeling – simulation – and em – Modeling by mathematical expression
Reexamination Certificate
2006-09-12
2006-09-12
Shah, Kamini (Department: 2128)
Data processing: structural design, modeling, simulation, and em
Modeling by mathematical expression
C382S224000, C703S001000, C703S006000, C703S022000
Reexamination Certificate
active
07107192
ABSTRACT:
Attributes of a data set to be employed in generating a predictive model are analyzed based on entropy, chi-square, or similar statistical measure. A target group of samples exhibiting one or more desired attributes is identified, then remaining attribute values for the target group are compared to corresponding attribute values for the whole sample population. A subset of all available attributes is then selected from those attributes which exhibit, when comparing attribute values of target group samples to attribute values for the whole sample population, the greatest relative difference or divergence. This subset is employed to generate the predictive model. Efficiency in generating the predictive model and the accuracy of the resulting predictive model is improved, since fewer attributes are employed and less computational resources are required.
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Cung Quan G.
Kolar Harry Roger
Norsworthy Kevin Eric
Ortega Julio
Scheibl Frederick J.
Dawkins Marilyn S.
Day Herng-der
Dillon & Yudell LLP
Shah Kamini
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