Augmented Naïve Bayesian Model of Classification Learning
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چکیده
The Naïve Bayesian Classifier and an Augmented Naïve Bayesian Classifier are applied to human classification tasks. The Naïve Bayesian Classifier is augmented with feature construction using a Galois lattice. The best features, measured on their withinand between-category overlap, are added to the category’s concept description. The results show that space efficient concept descriptions can predict much of the variance in the classification phenomena.
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تاریخ انتشار 2003