Anomaly detection of high-dimensional data based on Ensemble GANs with Dropout

Wanghu Chen, Jilong Yao,Meilin Zhou, Jing Li, Mengyang Shen

2022 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT)（2022）

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摘要

An unsupervised anomaly detection approach DGANs is proposed based on ensemble GANs with Dropout. The comparisons with representative approaches on 10 public datasets show it has advantages in accuracy, recall and F1 scores. DGANs can address the overfitting problem in ensemble GANs training on high-dimensional datasets.

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关键词

anomaly detection,high-dimensional data,Generative Adversarial Network (GAN),Dropout

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