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R: Data Analysis and Visualization by Ágnes Vidovics-Dancs, Kata Váradi, Tamás Vadász, Ágnes Tuza, Balázs Árpád Szucs, Julia Molnár, Péter Medvegyev, Balázs Márkus, István Margitai, Péter Juhász, Dániel Havran, Gergely Gabler, Barbara Dömötör, Gergely Daróczi, Ádám Banai, Milán Badics, Ferenc Illés, Edina Berlinger, Bater Makhabel, Hrishi V. Mittal, Jaynal Abedin, Brett Lantz, Tony Fischetti

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Intrusion detection and density-based methods

Here is a formal definition of outliers formalized based on concepts such as, LOF, LRD, and so on. Generally speaking, an outlier is a data point biased from others so much that it seems as if it has not been generated from the same distribution functions as others have been.

Given a dataset, D, a DB (x, y)-outlier, p, is defined like this:

Intrusion detection and density-based methods

The k-distance of the p data point denotes the distance between p and the data point, o, which is member of D:

Intrusion detection and density-based methods

The k-distance neighborhood of the p object is defined as ...

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