amelie 0.2.1

Anomaly Detection with Normal Probability Functions

Released Mar 18, 2019 by Dmitriy Bolotov

This package can be loaded by Renjin but 1 out 3 tests failed. An older version of this package is more compatible with Renjin.

Implements anomaly detection as binary classification for cross-sectional data. Uses maximum likelihood estimates and normal probability functions to classify observations as anomalous. The method is presented in the following lecture from the Machine Learning course by Andrew Ng: , and is also described in: Aleksandar Lazarevic, Levent Ertoz, Vipin Kumar, Aysel Ozgur, Jaideep Srivastava (2003) .



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    <name>bedatadriven public repo</name>

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This package was last tested against Renjin 0.9.2725 on Mar 26, 2019.



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