A Note on the Formal Implementation of the K-means Algorithm with Hard Positive and Negative Constraints

Igor Melnykov, Volodymyr Melnykov

Research output: Contribution to journalArticle

Abstract

The paper discusses a new approach for incorporating hard constraints into the K-means algorithm for semi-supervised clustering. An analytic modification of the objective function of K-means is proposed that has not been previously considered in the literature.

Original languageEnglish
JournalJournal of Classification
DOIs
Publication statusAccepted/In press - Jan 1 2020
Externally publishedYes

Keywords

  • Hard constraints
  • K-means
  • Semi-supervised clustering

ASJC Scopus subject areas

  • Mathematics (miscellaneous)
  • Psychology (miscellaneous)
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences

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