Results 281 to 290 of about 1,042,888 (328)
Online Conditional Outlier Detection in Nonstationary Time Series.
, 2017 Siqi Liu, Adam Wright, Miloš Hauskrecht
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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 +2 more
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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 +2 more
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Hastings Center Report, 2013
AbstractAmy's excellent home care was the only reason she was doing as well as she was. There was no one better at taking care of Amy than her husband. When she had a respiratory infection, Steve managed the necessary increased suctioning, nebulizer treatments, and ventilator, in addition to all the other intimate personal assistance she needed on a ...
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AbstractAmy's excellent home care was the only reason she was doing as well as she was. There was no one better at taking care of Amy than her husband. When she had a respiratory infection, Steve managed the necessary increased suctioning, nebulizer treatments, and ventilator, in addition to all the other intimate personal assistance she needed on a ...
openaire +2 more sources
Outliers—Part 2:Pitfalls in Detecting Outliers
2018Howard Mark, Jerry Workman
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Multivariate Outliers: A Conceptual and Practical Overview for the Nurse and Health Researcher
Canadian Journal of Nursing Research, 2021Maher M El-Masri, Fabrice Mowbray MScN
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2018
We use Hubble Space Telescope multicolour photometry of the globular cluster 47 Tucanae to uncover a population of 24 objects with no previous classification that are outliers from the single-star model tracks in the colour-magnitude diagram and yet are likely cluster members.
Campos, Fabiola +13 more
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We use Hubble Space Telescope multicolour photometry of the globular cluster 47 Tucanae to uncover a population of 24 objects with no previous classification that are outliers from the single-star model tracks in the colour-magnitude diagram and yet are likely cluster members.
Campos, Fabiola +13 more
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Cellular Metabolism and Disease: What Do Metabolic Outliers Teach Us?
Cell, 2012Ralph J Deberardinis
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