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Exploring Contemporary Approaches to Outlier Detection: Literature Review
  • Maciej Celiński,
  • Adam Kiersztyn
Maciej Celiński
Politechnika Lubelska

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Adam Kiersztyn
Politechnika Lubelska
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Abstract

This comprehensive review article delves into the evolving landscape of outlier detection techniques, shedding light on their significance in modern data analysis. In an era characterized by advanced technology and dynamic digital environments, the demand for robust anomaly detection methods spans across diverse domains. Anomaly detection plays a pivotal role in streamlining data analysis, saving valuable time, and offering versatile applicability across various data types. It encompasses an array of methods and approaches, each contributing to our understanding of data irregularities. This paper explores these techniques, emphasizing their role in the broader context of fuzzy methods’ applications. Furthermore, it provides an invaluable resource for those seeking a holistic review of the existing literature in this field. By examining current trends in the use of fuzzy methods and their potential impact on different facets of human life and the environment.