AI RESEARCH
Structure of Classifier Boundaries: Case Study for a Naive Bayes Classifier
arXiv CS.LG
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ArXi:2212.04382v5 Announce Type: replace-cross For a Bayes classifier whose input space is a graph, we study the structure of the boundary, which comprises those points for which at least one neighbor is classified differently. The scientific setting is assignment of DNA reads produced by next generations sequencers to candidate source genomes. We show that the boundary is both large and complicated in structure.