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various non-parametric clustering models to detect outliers, and assesses their effectiveness using different quality criDer … Clustering-Modelle, um auffällige Werte aufzudecken und nach verschiedenen Gütekriterien deren Wirkung zu bewerten. Als geeignet … various non-parametric clustering models to detect outliers, and assesses their effectiveness using different quality criteria …
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We propose new tools for visualizing large numbers of functional data in the form of smooth curves or surfaces. The proposed tools include functional versions of the bagplot and boxplot, and make use of the first two robust principal component scores, Tukey's data depth and highest density...
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Outlier detection targets those exceptional data whose pattern is rare and lie in low density regions. In this paper, under the assumption of complete spatial randomness inside clusters, we propose an MDV (Multi-scale Deviation of the Volume) approach to identifying outliers. In addition to...
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