Sarcouncil Journal of Engineering and Computer Sciences

Sarcouncil Journal of Engineering and Computer Sciences

An Open access peer reviewed international Journal
Publication Frequency- Monthly
Publisher Name-SARC Publisher

ISSN Online- 2945-3585
Country of origin-PHILIPPINES
Impact Factor- 3.7
Language- English

Keywords

Editors

Anomaly Detection: Principles, Methods, and Applications in Modern Data Analytics

Keywords: Outlier detection, pattern recognition, fraud detection, predictive maintenance, machine learning.

Abstract: The article gives a thorough description of anomaly detection, which is important in data analytics since it looks for anything unusual in a set of data. The article discusses the important rules for finding outliers, describes different anomaly detection techniques, and studies where it is used in finance, cybersecurity, manufacturing, healthcare, and retail. Current knowledge and techniques used in anomaly detection make this article useful for those wanting to build systems that catch anomalies in diverse fields.

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