TAN network classifers for fMRI data

Abstract

The goal of this work is to try a new solution for the classification task of predicting when a subject is reading a sentence versus perceiving a picture using brain imaging data (fMRI). fTAN, an algorithm that both relaxes the conditional independence assumptions from a traditional Naive Bayes classifier, and assumes continuous variables, is implemented… (More)

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Cite this paper

@inproceedings{AshleyRollman2006TANNC, title={TAN network classifers for fMRI data}, author={Michael P. Ashley-Rollman and Lucia Castellanos P{\'e}rez-Bolde}, year={2006} }