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 journalArticlepeer-review

1 Scopus citations

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 (US)
Pages (from-to)789-809
Number of pages21
JournalJournal of Classification
Volume37
Issue number3
DOIs
StatePublished - Oct 2020

Keywords

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

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