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 (US) |
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Pages (from-to) | 789-809 |
Number of pages | 21 |
Journal | Journal of Classification |
Volume | 37 |
Issue number | 3 |
DOIs | |
State | Published - Oct 2020 |
Bibliographical note
Publisher Copyright:© 2020, The Classification Society.
Keywords
- Hard constraints
- K-means
- Semi-supervised clustering