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Multiple outlier detection revisited

delete1998-07-01
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B
Beata Walczak
D
D.L. Massart
DOI:10.1016/S0169-7439(98)00034-3delete
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摘要

摘要

En 中文
The discrimination power of the classical or/and robust diagnostics for the 34 (real and simulated) regression data sets with multiple outliers is compared. These diagnostics, presented in the uniform way for the large number of objects, are then used in the pattern recognition approaches (PLS, Neural Networks, Rough Set Theory) to estimate the joint discrimination power of the classical or/and robust diagnostics and to construct models (or logical rules), allowing identification of outliers in the new data sets. (C) 1998 Elsevier Science B.V. All rights reserved.
Keyword:
regression outlier identification
rough set theory
neural networks
PLS
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Chemometrics and Intelligent Laboratory Systems 封面图
Chemometrics and Intelligent Laboratory Systems
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3.8
论文数:
4.6K
被引数:
1.2W

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