Machine learning
Label Propagation
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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Sources
- Zhu, X., & Ghahramani, Z. (2002). Learning from labeled and unlabeled data with label propagation. Technical Report CMU-CALD-02-107, Carnegie Mellon University. link ↗
- Zhu, X., Ghahramani, Z., & Lafferty, J. (2003). Semi-supervised learning using Gaussian fields and harmonic functions. Proceedings of the 20th International Conference on Machine Learning (ICML-2003), pp. 912–919. DOI: 10.5555/3041838.3041953 ↗
- Chapelle, O., Scholkopf, B., & Zien, A. (Eds.) (2006). Semi-Supervised Learning. MIT Press. ISBN: 978-0-262-03358-9
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Online Semi-supervised learningRegularized semi-supervised learningSelf-supervised Active LearningSelf-supervised Decision TreeSelf-supervised Random ForestSelf-supervised Support Vector MachineSemi-supervised Active LearningSemi-supervised Association RulesSemi-supervised BaggingSemi-supervised BoostingSemi-supervised Decision TreeSemi-supervised Doc2VecSemi-supervised Gaussian Mixture ModelSemi-supervised Graph Neural NetworkSemi-supervised K-nearest neighborsSemi-supervised Linear RegressionSemi-supervised Logistic RegressionSemi-supervised Online LearningSemi-supervised Random ForestSemi-supervised Stacking EnsembleSemi-supervised Support Vector MachineSemi-supervised Transfer LearningSemi-supervised XGBoostWeakly supervised graph neural network