পদ্ধতির তুলনা করুন

	স্ব-পর্যবেক্ষিত সিদ্ধান্ত বৃক্ষ	লেবেল প্রোপাগেশন
ক্ষেত্র	যন্ত্র শিখন	যন্ত্র শিখন
পরিবার	Machine learning	Machine learning
উদ্ভবের বছর	2015–present	2002
প্রবর্তক	Multiple authors (active research area, 2010s–2020s)	Zhu, X. & Ghahramani, Z.
ধরন	Self-supervised ensemble/single tree model	Graph-based semi-supervised classification
মৌলিক উৎস	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.
অপর নাম	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
সম্পর্কিত	5	3
সারসংক্ষেপ	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.