Mimicking Learning for 1-NN Classifiers

Przemysław Śliwiński, Paweł Wachel, Jerzy W. Rozenblit

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We consider the problem of mimicking the behavior of the nearest neighbor algorithm with an unknown distance measure. Our goal is, in particular, to design and update a learning set so that two NN algorithms with various distance functions ρp and ρq, 0 < p, q< ∞, classify in the same way, and to approximate the behavior of one classifier by the other. The autism disorder-related motivation of the problem is presented.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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