방법 비교

	준지도 K-최근접 이웃 (Semi-supervised K-Nearest Neighbors)	레이블 전파
분야	머신러닝	머신러닝
계열	Machine learning	Machine learning
기원 연도	2002 (semi-supervised extension); 1967 (KNN base)	2002
창시자	Zhu, X. & Ghahramani, Z. (label propagation); Cover, T. & Hart, P. (KNN base)	Zhu, X. & Ghahramani, Z.
유형	Semi-supervised classifier / label propagation	Graph-based semi-supervised classification
원전	Zhu, X. & Ghahramani, Z. (2002). Learning from labeled and unlabeled data with label propagation. Technical Report CMU-CALD-02-107, Carnegie Mellon University.	Zhu, X., & Ghahramani, Z. (2002). Learning from labeled and unlabeled data with label propagation. Technical Report CMU-CALD-02-107, Carnegie Mellon University.
별칭	SS-KNN, semi-supervised KNN, KNN label propagation, graph-based semi-supervised KNN	LP, label spreading, graph-based semi-supervised learning, harmonic label propagation
관련	4	3
요약	Semi-supervised KNN extends the classic K-nearest neighbors algorithm to exploit large pools of unlabeled data alongside a small labeled set. By building a KNN graph over all observations and propagating known labels through the graph's edges, the method infers labels for unlabeled points without requiring expensive manual annotation of every sample.	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.