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Enhancing Outlier Detection by an Outlier Indicator

2018
Outlier detection is an important task in data mining and has high practical value in numerous applications such as astronomical observation, text detection, fraud detection and so on. At present, a large number of popular outlier detection algorithms are available, including distribution-based, distance-based, density-based, and clustering-based ...
Xiaqiong Li, Xiaochun Wang, Xia Li Wang
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Outlier detection

Proceedings of the International Conference on Artificial Intelligence, Information Processing and Cloud Computing, 2019
Outlier detection is a fundamental issue in data mining and machine learning. Most methods calculate outlier score for each object and then threshold the scores to detect outliers. Most widely used thresholding techniques are based on statistics like standard deviation around mean, median absolute deviation and interquartile range. Unfortunately, these
Jiawei Yang 0001   +2 more
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Separability with Outliers

2005
We develop exact and approximate algorithms for computing optimal separators and measuring the extent to which two point sets in d-dimensional space are separated, with respect to different classes of separators and various extent measures. This class of geometric problems generalizes two widely studied problem families, namely separability and the ...
Sariel Har-Peled, Vladlen Koltun
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Shape fitting with outliers

Proceedings of the nineteenth conference on Computational geometry - SCG '03, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sariel Har-Peled, Yusu Wang 0001
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Outlier or not?

2023
Already facing over $400 billion in reconstruction costs in 2023 and an ongoing war, Ukraine confronts seemingly insurmountable challenges for EU accession. Even without compensating for war damages, the financial burden of aligning with the EU is significant.
Bertelsmann Stiftung   +1 more
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Making Sense of Outliers

Phonetica, 2012
AbstractPhonetic inquiry, particularly of the kind which looks at large numbers of items, frequently asks what a ‘typical’ example of a phenomenon of speech is like. For example, in describing the plosives of a language, it is common to calculate average closure durations or voice onset times in some contexts.
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Robust Statistical Scaling of Outlier Scores: Improving the Quality of Outlier Probabilities for Outliers

Outlier detection algorithms typically assign an outlier score to each observation in a dataset, indicating the degree to which an observation is an outlier. However, these scores are often not comparable across algorithms and can be difficult for humans to interpret.
Philipp Röchner   +4 more
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Outlier … … …. s

Technometrics, 1983
R. J. Beckman, R. D. Cook
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Multivariate Outliers: A Conceptual and Practical Overview for the Nurse and Health Researcher

Canadian Journal of Nursing Research, 2021
Maher M El-Masri, Fabrice I Mowbray
exaly  

Outliers

Notes and Queries
Abstract The penultimate chapter is an examination of the odd cases. It takes a closer look at the outlier locales, those areas where population decline does not produce a more progressive electorate and those areas where population growth seems to advantage Republicans at the expense of Democrats.
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