Structure of Classifier Boundaries: Case Study for a Naive Bayes Classifier

Whether based on models, training data or a combination, classifiers place (possibly complex) input data into one of a relatively small number of output categories. In this paper, we study the structure of the boundary--those points for which a neighbor is classified differently--in the context of an input space that is a graph, so that there is a concept of neighboring inputs, The scientific setting is a model-based naive Bayes classifier for DNA reads produced by Next Generation Sequencers. We …

bayes case case study classifier classifiers combination context cs.lg data paper small space stat.ml study training training data