Machine learningMachine learning

Bayesian k-Nearest Neighbors

Bayesian k-Nearest Neighbors (Bayesian KNN) extends the classical KNN algorithm by placing a prior distribution over the neighborhood size k and combining likelihood evidence from neighbors with that prior to produce calibrated posterior class probabilities. It retains KNN's intuitive instance-based logic while adding principled uncertainty quantification over predictions.

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Sources

  1. Holmes, C. C., & Adams, N. M. (2002). A probabilistic nearest neighbour method for statistical pattern recognition. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 64(2), 295–306. DOI: 10.1111/1467-9868.00338
  2. K-nearest neighbors algorithm. Wikipedia. link

Related methods

ScholarGateBayesian k-nearest neighbors (Bayesian k-Nearest Neighbors Classifier). Retrieved 2026-06-04 from https://scholargate.app/en/machine-learning/bayesian-k-nearest-neighbors