The Inverse Bagging Algorithm: Anomaly Detection by Inverse Bootstrap Aggregating

24 Nov 2016 Pietro Vischia Tommaso Dorigo

For data sets populated by a very well modeled process and by another process of unknown probability density function (PDF), a desired feature when manipulating the fraction of the unknown process (either for enhancing it or suppressing it) consists in avoiding to modify the kinematic distributions of the well modeled one. A bootstrap technique is used to identify sub-samples rich in the well modeled process, and classify each event according to the frequency of it being part of such sub-samples... (read more)

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