قارن الطرق

	التجميع الطبقي شبه المُشرف عليه	انتشار التسمية
المجال	تعلم الآلة	تعلم الآلة
العائلة	Machine learning	Machine learning
سنة النشأة	2000s–2010s	2002
صاحب الطريقة	Combines Wolpert (1992) stacking with semi-supervised learning principles	Zhu, X. & Ghahramani, Z.
النوع	Ensemble (stacked generalization with unlabeled data augmentation)	Graph-based semi-supervised classification
المصدر التأسيسي	Wolpert, D. H. (1992). Stacked generalization. Neural Networks, 5(2), 241–259.	Zhu, X., & Ghahramani, Z. (2002). Learning from labeled and unlabeled data with label propagation. Technical Report CMU-CALD-02-107, Carnegie Mellon University.
الأسماء البديلة	SSL stacking, semi-supervised stacked generalization, self-trained stacking, semi-supervised meta-learning ensemble	LP, label spreading, graph-based semi-supervised learning, harmonic label propagation
ذات صلة	5	3
الملخص	Semi-supervised Stacking Ensemble extends the classic stacked generalization framework to settings where only a fraction of training examples carry labels. Base learners are first trained on labeled data, then used to assign pseudo-labels to unlabeled examples; the expanded dataset trains stronger base models whose out-of-fold predictions form the input to a meta-learner, yielding a two-tier ensemble that exploits both labeled and unlabeled structure.	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.