Imbalanced SVM‐Based Anomaly Detection Algorithm for Imbalanced Training Datasets

Imbalanced SVM‐Based Anomaly Detection Algorithm for Imbalanced Training Datasets

Abnormal samples are usually difficult to obtain in production systems, resulting in imbalanced training sample sets. Namely, the number of positive samples is far less than the number of negative samples. Traditional Support Vector Machine (SVM)‐based anomaly detection algorithms perform poorly for...

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Bibliographic Details
Main Authors: GuiPing Wang, JianXi Yang, Ren Li
Format: Article
Language:English
Published: Electronics and Telecommunications Research Institute (ETRI) 2017-10-01
Series:ETRI Journal
Subjects:
Anomaly detection
Decision function
GMean
Imbalanced training sample set
Support vector machine (SVM)
Online Access:https://doi.org/10.4218/etrij.17.0116.0879

Internet

https://doi.org/10.4218/etrij.17.0116.0879

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