Mimicking Learning for 1-NN Classifiers

Przemysław Śliwiński, Paweł Wachel, Jerzy W. Rozenblit

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

Abstract

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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