So sánh phương pháp

	Cây quyết định tự giám sát	Lan truyền nhãn
Lĩnh vực	Học máy	Học máy
Họ	Machine learning	Machine learning
Năm ra đời	2015–present	2002
Người khởi xướng	Multiple authors (active research area, 2010s–2020s)	Zhu, X. & Ghahramani, Z.
Loại	Self-supervised ensemble/single tree model	Graph-based semi-supervised classification
Công trình gốc	Self-supervised learning. Wikipedia.	Zhu, X., & Ghahramani, Z. (2002). Learning from labeled and unlabeled data with label propagation. Technical Report CMU-CALD-02-107, Carnegie Mellon University.
Tên gọi khác	SSL decision tree, self-supervised tree classifier, pseudo-label decision tree, unsupervised-guided decision tree	LP, label spreading, graph-based semi-supervised learning, harmonic label propagation
Liên quan	5	3
Tóm tắt	Self-supervised Decision Tree learning combines the interpretability of classical decision trees with the ability to exploit large quantities of unlabeled data through self-supervised pretext tasks. The model learns useful feature representations or node-split criteria from unlabeled samples before refining predictions on a small labeled set, bridging the gap between fully supervised trees and purely unsupervised clustering.	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.