articleIEEE AccessJan 1, 2019GOLD OA

Progress in Outlier Detection Techniques: A Survey

Harbin Institute of Technology · Menoufia University

Indexed incrossrefdoaj

Abstract

Detecting outliers is a significant problem that has been studied in various research and application areas. Researchers continue to design robust schemes to provide solutions to detect outliers efficiently. In this survey, we present a comprehensive and organized review of the progress of outlier detection methods from 2000 to 2019. First, we offer the fundamental concepts of outlier detection and then categorize them into different techniques from diverse outlier detection techniques, such as distance-, clustering-, density-, ensemble-, and learning-based methods. In each category, we introduce some state-of-the-art outlier detection methods and further discuss them in detail in terms of their performance.…

Citation impact

506
total citations
FWCI
30.61
Percentile
100%
References
251
Citations per year

Authors

3

Topics & keywords

Keywords
  • Anomaly detection
  • Outlier
  • Computer science
  • Categorization
  • Cluster analysis
  • Data mining
  • Artificial intelligence
  • Machine learning
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