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Krahasoni metodat

Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.

K-means vetë-mbikëqyrës×K-means gjysmë-mbikëqyrës×
FushaMësimi i makinësMësimi i makinës
FamiljaMachine learningMachine learning
Viti i origjinës20182001–2002
KrijuesiCaron, M. et al. (DeepCluster framework)Wagstaff, K. et al. (constrained); Basu, S. et al. (seeded)
LlojiSelf-supervised clusteringSemi-supervised clustering
Burimi themeluesCaron, M., Bojanowski, P., Joulin, A., & Douze, M. (2018). Deep Clustering for Unsupervised Learning of Visual Features. In Proceedings of the European Conference on Computer Vision (ECCV), 132–149. link ↗Wagstaff, K., Cardie, C., Rogers, S., & Schroedl, S. (2001). Constrained K-means Clustering with Background Knowledge. In Proceedings of the 18th International Conference on Machine Learning (ICML 2001), pp. 577–584. link ↗
Emërtime të tjeraself-supervised clustering with K-means, deep clustering with K-means, unsupervised K-means with pseudo-labels, SSL K-meansconstrained K-means, seeded K-means, partially supervised K-means, SS-K-means
Të lidhura55
PërmbledhjaSelf-supervised K-means is a clustering technique that combines K-means assignment with self-supervised representation learning. The model alternates between clustering unlabeled data points into K groups and using those cluster assignments as pseudo-labels to refine an underlying feature representation, yielding increasingly coherent clusters without any human-annotated ground truth.Semi-supervised K-means extends standard K-means clustering by incorporating partial supervision — either a small set of labeled seed points or pairwise must-link and cannot-link constraints — to guide cluster formation. It bridges unsupervised clustering and fully supervised classification, enabling more meaningful clusters when labels are scarce but costly to obtain in full.
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ScholarGateKrahasoni metodat: Self-supervised K-means · Semi-supervised K-means. Marrë më 2026-06-18 nga https://scholargate.app/sq/compare