Iterative Nearest Neighborhood Oversampling in Semisupervised Learning from Imbalanced Data

Transductive graph-based semisupervised learning methods usually build an undirected graph utilizing both labeled and unlabeled samples as vertices. Those methods propagate label information of labeled samples to neighbors through their edges in order to get the predicted labels of unlabeled samples...

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Detalles Bibliográficos
Autores principales: Li, Fengqi, Yu, Chuang, Yang, Nanhai, Xia, Feng, Li, Guangming, Kaveh-Yazdy, Fatemeh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3725769/
https://www.ncbi.nlm.nih.gov/pubmed/23935439
http://dx.doi.org/10.1155/2013/875450

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3725769/
https://www.ncbi.nlm.nih.gov/pubmed/23935439
http://dx.doi.org/10.1155/2013/875450

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