This paper investigates the structure of classifier boundaries, specifically for a Naive Bayes classifier operating on graph-based input spaces. The research focuses on DNA read assignment to candidate genomes, demonstrating that the boundary is both extensive and complex. A novel uncertainty measure, Neighbor Similarity, is introduced, which correlates with existing uncertainty measures and can be applied to classifiers lacking inherent uncertainty quantification. AI
RANK_REASON This is a research paper published on arXiv detailing a specific statistical method. [lever_c_demoted from research: ic=1 ai=0.7]
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