A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data

Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in h...

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Detalles Bibliográficos
Autores principales: Song, Hongchao, Jiang, Zhuqing, Men, Aidong, Yang, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5706085/
https://www.ncbi.nlm.nih.gov/pubmed/29270197
http://dx.doi.org/10.1155/2017/8501683

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5706085/
https://www.ncbi.nlm.nih.gov/pubmed/29270197
http://dx.doi.org/10.1155/2017/8501683

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