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When is an outlier not an outlier?
NIR news, 2019The tendency of the users of NIRS is to think of the composition particularly in terms of the reference data, for the prediction of which the technique is to be used. The concept and principle of NIRS analysis differ from classical chemical analysis in that NIRS is based exclusively on the spectra.
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WIREs Data Mining and Knowledge Discovery, 2011
AbstractOutlier detection is an area of research with a long history which has applications in many fields. This article provides a nontechnical and concise overview of the commonly used approaches for detecting outliers, including classical methods, new challenges posed by real‐world massive data, and some of the key advances made in recent years ...
Xiaogang Su, Chih-Ling Tsai
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AbstractOutlier detection is an area of research with a long history which has applications in many fields. This article provides a nontechnical and concise overview of the commonly used approaches for detecting outliers, including classical methods, new challenges posed by real‐world massive data, and some of the key advances made in recent years ...
Xiaogang Su, Chih-Ling Tsai
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Enhancing Outlier Detection by an Outlier Indicator
2018Outlier 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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IEEE Transactions on Knowledge and Data Engineering
Outliers carry significant information to reflect an anomaly mechanism, so outlier detection facilitates relevant data mining. In terms of outlier detection, the classical approaches from distances apply to numerical data rather than nominal data, while ...
Xianyong Zhang, Zhong Yuan, Duoqian Miao
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Outliers carry significant information to reflect an anomaly mechanism, so outlier detection facilitates relevant data mining. In terms of outlier detection, the classical approaches from distances apply to numerical data rather than nominal data, while ...
Xianyong Zhang, Zhong Yuan, Duoqian Miao
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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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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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ACM Computing Surveys, 2020
Over the past decade, we have witnessed an enormous amount of research effort dedicated to the design of efficient outlier detection techniques while taking into consideration efficiency, accuracy, high-dimensional data, and distributed environments ...
A. Boukerche, Lining Zheng, O. Alfandi
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Over the past decade, we have witnessed an enormous amount of research effort dedicated to the design of efficient outlier detection techniques while taking into consideration efficiency, accuracy, high-dimensional data, and distributed environments ...
A. Boukerche, Lining Zheng, O. Alfandi
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Outlier Resistant Unsupervised Deep Architectures for Attributed Network Embedding
Web Search and Data Mining, 2020Attributed network embedding is the task to learn a lower dimensional vector representation of the nodes of an attributed network, which can be used further for downstream network mining tasks.
S. Bandyopadhyay +3 more
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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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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sariel Har-Peled, Yusu Wang 0001
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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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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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Outlier detection using isolation forest and local outlier factor
Research in Adaptive and Convergent Systems, 2019Outlier detection, also named as anomaly detection, is one of the hot issues in the field of data mining. As well-known outlier detection algorithms, Isolation Forest(iForest) and Local Outlier Factor(LOF) have been widely used.
Zhangyu Cheng +2 more
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