Process and system for developing a predictive model

Data processing: artificial intelligence – Machine learning – Genetic algorithm and genetic programming system

Reexamination Certificate

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C706S012000, C706S014000

Reexamination Certificate

active

07043461

ABSTRACT:
The present invention relates to a computer implemented process for developing a model which predicts the value of a single dependent variable based on the value of at least one independent variable. The process comprises the steps of creating a dataset containing a plurality of observations each containing a value for the dependent variable and values for the at least one independent variable, creating from the dataset a plurality of original chromosomes each comprising a possible predictive model, developing a quantitative fitness measure for each chromosome, and creating a new generation of chromosomes by selecting a number of the original chromosomes based upon the fitness measures, crossing the selected original chromosomes by at least one of a cloning and a pure (standard) crossover technique, and mutating the crossed chromosomes. A system for carrying out the process of the present invention is also described.

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“GENOCOP: A Genetic Algorithm for Numerical Optimization Problems with Linear Constraints”, by Zbigniew Michalewicz et al., Communications of the ACM, published by AMC Press, New York, NY, 1996, vol. 39, issue 12es, pp. 1-27.

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