Augmented naive bayesian model of classification learning
Lewis J. Frey, Douglas Fisher · eScholarship (California Digital Library) · 2003
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 within- and 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.