Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Mësimi gjysmë-mbikëqyrur i rregulluar× | Propagimi i Etiketimeve× | |
|---|---|---|
| Fusha | Mësimi i makinës | Mësimi i makinës |
| Familja | Machine learning | Machine learning |
| Viti i origjinës≠ | 2006 | 2002 |
| Krijuesi≠ | Belkin, M.; Niyogi, P.; Sindhwani, V. | Zhu, X. & Ghahramani, Z. |
| Lloji≠ | Regularized learning paradigm | Graph-based semi-supervised classification |
| Burimi themelues≠ | Belkin, M., Niyogi, P., & Sindhwani, V. (2006). Manifold regularization: A geometric framework for learning from labeled and unlabeled examples. Journal of Machine Learning Research, 7, 2399–2434. link ↗ | Zhu, X., & Ghahramani, Z. (2002). Learning from labeled and unlabeled data with label propagation. Technical Report CMU-CALD-02-107, Carnegie Mellon University. link ↗ |
| Emërtime të tjera | manifold regularization, graph-regularized SSL, semi-supervised regularization, Laplacian regularization | LP, label spreading, graph-based semi-supervised learning, harmonic label propagation |
| Të lidhura≠ | 6 | 3 |
| Përmbledhja≠ | Regularized semi-supervised learning adds explicit geometric or graph-based penalty terms to a semi-supervised objective so that the decision function varies smoothly over the data manifold. Pioneered through manifold regularization (Belkin, Niyogi & Sindhwani, 2006), it exploits the structure of both labeled and unlabeled examples to learn more accurate models than supervised regularization alone when labeled data are scarce. | Label Propagation is a graph-based semi-supervised learning algorithm introduced by Zhu and Ghahramani in 2002 that spreads class labels from a small set of labeled nodes to a large set of unlabeled nodes by iteratively diffusing label information along the edges of a similarity graph, exploiting the manifold structure of the data. |
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