System and method for generating a classifier model for...

Data processing: artificial intelligence – Neural network – Learning task

Reexamination Certificate

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C706S059000

Reexamination Certificate

active

07949622

ABSTRACT:
Generally, the present invention provides a method and computerized system for generating a classifier model, wherein the classifier model is operative to classify web content. The method and computerized system includes a first step of defining a plurality of predictive performance measures based on a leave one out (LOO) cross validation in terms of selectable model parameters. Exemplary predictive performance measures includes smoothened predictive measures such as F-measure, weighted error rate measure, area under curve measure, by way of example. The method and computerized system further includes deriving efficient analytical expressions for predictive performance measures to compute the LOO predictive performance and their derivatives. The next step is thereupon selecting a classifier model based on the LOO predictive performance.

REFERENCES:
Cawley, G.C., Leave-One-Out Cross-Validation Based Model Selection Criteria for Weighted LS-SVMs, 2006 International Joint Conference on Neural Networks, pp. 1661-1668, Jul. 16-21, 2006.

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