A hybrid anomaly detection method for high dimensional data

Anomaly detection of high-dimensional data is a challenge because the sparsity of the data distribution caused by high dimensionality hardly provides rich information distinguishing anomalous instances from normal instances. To address this, this article proposes an anomaly detection method combinin...

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Vydané v:	PeerJ. Computer science Ročník 9; s. e1199
Hlavní autori:	Zhang, Xin, Wei, Pingping, Wang, Qingling
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States PeerJ, Inc 12.01.2023 PeerJ Inc
Predmet:	Algorithms and Analysis of Algorithms Anomalies Anomaly detection Autoencoder Classification Data compression Data Mining and Machine Learning Data Science Feature extraction High-dimensional data Least squares Support vector machine Support vector machines High-dimensional data Support vector machine Autoencoder Anomaly detection
ISSN:	2376-5992, 2376-5992
On-line prístup:	Získať plný text
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