Krahasoni metodat

	Pema e vendimit e vetë-mbikëqyrur	Mësimi Gjysmë i Mbikëqyrur
Fusha	Mësimi i makinës	Mësimi i makinës
Familja	Machine learning	Machine learning
Viti i origjinës	2015–present	1970s–2006 (formalized)
Krijuesi	Multiple authors (active research area, 2010s–2020s)	Vapnik, V. N. and others (community of researchers, 1970s–2000s)
Lloji	Self-supervised ensemble/single tree model	Learning paradigm
Burimi themelues	Self-supervised learning. Wikipedia.	Chapelle, O., Scholkopf, B., & Zien, A. (Eds.) (2006). Semi-Supervised Learning. MIT Press. ISBN: 978-0-262-03358-9
Emërtime të tjera	SSL decision tree, self-supervised tree classifier, pseudo-label decision tree, unsupervised-guided decision tree	SSL, semi-supervised machine learning, transductive learning, label-efficient learning
Të lidhura	5	5
Përmbledhja	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.	Semi-supervised learning (SSL) is a machine learning paradigm that trains models using a small set of labeled examples together with a much larger pool of unlabeled data. By leveraging the structure inherent in unlabeled data, SSL achieves accuracy closer to fully supervised models while requiring far fewer costly manual labels — making it practical when labeling is expensive, slow, or resource-constrained.