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

Igor Melnykov; Volodymyr Melnykov

doi:10.1007/s00357-019-09349-x

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 journal › Article

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 language	English
Journal	Journal of Classification
DOIs	https://doi.org/10.1007/s00357-019-09349-x
Publication status	Accepted/In press - Jan 1 2020
Externally published	Yes

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Keywords

Hard constraints
K-means
Semi-supervised clustering

ASJC Scopus subject areas

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

Cite this

Melnykov, I., & Melnykov, V. (Accepted/In press). A Note on the Formal Implementation of the K-means Algorithm with Hard Positive and Negative Constraints. Journal of Classification. https://doi.org/10.1007/s00357-019-09349-x

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Access to Document

10.1007/s00357-019-09349-x