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)|
|Number of pages||21|
|Journal||Journal of Classification|
|State||Published - Oct 2020|
Bibliographical notePublisher Copyright:
© 2020, The Classification Society.
- Hard constraints
- Semi-supervised clustering