Bayesian instance selection for the nearest neighbor rule

  title={Bayesian instance selection for the nearest neighbor rule},
  author={Sylvain Ferrandiz and Marc Boull{\'e}},
  journal={Machine Learning},
The nearest neighbors rules are commonly used in pattern recognition and statistics. The performance of these methods relies on three crucial choices: a distance metric, a set of prototypes and a classification scheme. In this paper, we focus on the second, challenging issue: instance selection. We apply a maximum a posteriori criterion to the evaluation of sets of instances and we propose a new optimization algorithm. This gives birth to Eva, a new instance selection method. We benchmark this… CONTINUE READING


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