A Survey of Outlier Detection Methodologies

2004/10/01 by Joanna Hodge, Victoria Hodge, Jim Austin · 8 citations
Computer Science · #Anomaly Detection Techniques and Applications #Anomaly detection #Artificial intelligence #Computer science #Data mining #Data set #Imbalanced Data Classification Techniques #Machine Learning and Data Classification #Outlier #Set (abstract data type)

paper · doi:10.1023/b:aire.0000045502.10941.a9

crossref issued 2004/10/01 · crossref published 2004/10/01 · crossref published-print 2004/10/01 · openalex publication_date 2004/10/01 · crossref created 2004/10/22 · crossref deposited 2025/05/18 · openalex created_date 2025/10/10 · crossref indexed 2026/08/04 · openalex updated_date 2026/08/04

Citations

• Procedures for Detecting Outlying Observations in Samples
• Novelty detection and neural network validation
• Efficient algorithms for mining outliers from large data sets

Cited by

• Data-driven Soft Sensors in the process industry
• A Rank-SVM Approach to Anomaly Detection
• Fast and Exact Outlier Detection in Metric Spaces: A Proximity Graph-based Approach
• Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
• Uncovering Plagiarism Networks
• REMIX: Automated Exploration for Interactive Outlier Detection
• Anomaly Detection Based on Zero-Shot Outlier Synthesis and Hierarchical Feature Distillation
• Outlier [wikipedia]