Cross-validation for naive bayes data mining model

Details Cross-validation for naive bayes data mining model Cross-validation for naive bayes data mining model

2007-11-20

2007-11-20

Hirl, Joseph P (Department: 2129)

Data processing: artificial intelligence

Knowledge processing system

C706S014000, C706S012000

Reexamination Certificate

active

10419761

ABSTRACT:
A system, method, and computer program product provides a useful measure of the accuracy of a Naïve Bayes predictive model and reduced computational expense relative to conventional techniques. A method for measuring accuracy of a Naïve Bayes predictive model comprises the steps of receiving a training dataset comprising a plurality of rows of data, building a Naïve Bayes predictive model using the training dataset, for each of at least a portion of the plurality of rows of data in the training dataset incrementally untraining the Naïve Bayes predictive model using the row of data and determining an accuracy of the incrementally untrained Naïve Bayes predictive model, and determining an aggregate accuracy of the Naïve Bayes predictive model.

REFERENCES:
patent: 6182058 (2001-01-01), Kohavi
patent: 6278464 (2001-08-01), Kohavi et al.
patent: 6460049 (2002-10-01), Becker et al.
patent: 6807491 (2004-10-01), Pavlovic et al.
patent: 2003/0077586 (2003-04-01), Pavlovic et al.
patent: 2003/0176931 (2003-09-01), Pednault et al.

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