Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
Jennifer Neville, Brian Gallagher, Tina Eliassi-Ra...
We begin by reviewing current spatial approaches to CSCW (mediaspaces, spatial video conferencing, collaborative virtual environments and telepresence applications) and classifyin...
Steve Benford, Chris Brown, Gail Reynard, Chris Gr...
Feature Space Conversion for classifiers is the process by which the data that is to be fed into the classifier is transformed from one form to another. The motivation behind doin...