Analyzing outliers cautiously

IEEE Transactions on Knowledge and Data Engineering

Volumn 14, Issue 2, 2002, Pages 432-437

  Liu, Xiaohui ^a   Cheng, Gongxian ^b   Wu, John X ^c  

^a BRUNEL UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF LONDON   (United Kingdom)

^c MOORFIELDS EYE HOSPITAL   (United Kingdom)

Author keywords

Al modeling; Domain knowledge; Outliers; Self organizing maps

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL METHODS; DATA REDUCTION; ERROR ANALYSIS; MATHEMATICAL MODELS; SELF ORGANIZING MAPS; STATISTICAL METHODS;

DOMAIN KNOWLEDGE;

KNOWLEDGE BASED SYSTEMS;

EID: 0036509958     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/69.991726     Document Type: Article

References (20)

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2. Identifying and eliminating mislabeled training instances
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4. The subjective nature of outlier rejection procedures
5. Robust estimates, residuals and outlier detection with multi-response data
6. The meaning and use of the area under a receiver operator curve
7. Representing points in many dimensions by trees and castles (with discussion)
8. A unified notion of outliers: Properties and computation
9. Identifying the measurement noise in glaucomatous testing: An artificial neural network approach
10. Noise and uncertainty management in intelligent data modeling
11. Computer aided cleaning of large databases for character recognition