Probabilistic Nearest Neighbors Classification

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Resumo

Analysis of the currently established Bayesian nearest neighbors classification model points to a connection between the computation of its normalizing constant and issues of NP-completeness. An alternative predictive model constructed by aggregating the predictive distributions of simpler nonlocal models is proposed, and analytic expressions for the normalizing constants of these nonlocal models are derived, ensuring polynomial time computation without approximations. Experiments with synthetic and real datasets showcase the predictive performance of the proposed predictive model.

Palavras-chave

Probabilistic machine learning; Nearest neighbors classification; NP-completeness
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Entropy
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Inglês

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Área do Conhecimento CNPQ

CIENCIAS EXATAS E DA TERRA::MATEMATICA

CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA

ENGENHARIAS::ENGENHARIA ELETRICA

CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO

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