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...
Main Authors: | GuiPing Wang, JianXi Yang, Ren Li |
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Format: | Article |
Language: | English |
Published: |
Electronics and Telecommunications Research Institute (ETRI)
2017-10-01
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Series: | ETRI Journal |
Subjects: | |
Online Access: | https://doi.org/10.4218/etrij.17.0116.0879 |
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