Progress in Outlier Detection Techniques: A Survey
Harbin Institute of Technology · Menoufia University
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
- FWCI
- 30.61
- Percentile
- 100%
- References
- 251
Authors
3Topics & keywords
- Anomaly detection
- Outlier
- Computer science
- Categorization
- Cluster analysis
- Data mining
- Artificial intelligence
- Machine learning