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Comparar métodos

Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

K-Vizinhos Mais Próximos Semi-supervisionado×Propagação de Rótulos×
ÁreaAprendizado de máquinaAprendizado de máquina
FamíliaMachine learningMachine learning
Ano de origem2002 (semi-supervised extension); 1967 (KNN base)2002
Autor originalZhu, X. & Ghahramani, Z. (label propagation); Cover, T. & Hart, P. (KNN base)Zhu, X. & Ghahramani, Z.
TipoSemi-supervised classifier / label propagationGraph-based semi-supervised classification
Fonte seminalZhu, X. & Ghahramani, Z. (2002). Learning from labeled and unlabeled data with label propagation. Technical Report CMU-CALD-02-107, Carnegie Mellon University. link ↗Zhu, X., & Ghahramani, Z. (2002). Learning from labeled and unlabeled data with label propagation. Technical Report CMU-CALD-02-107, Carnegie Mellon University. link ↗
Outros nomesSS-KNN, semi-supervised KNN, KNN label propagation, graph-based semi-supervised KNNLP, label spreading, graph-based semi-supervised learning, harmonic label propagation
Relacionados43
ResumoSemi-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.
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ScholarGateComparar métodos: Semi-supervised K-nearest neighbors · Label Propagation. Recuperado em 2026-06-19 de https://scholargate.app/pt/compare