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Anomaly Detection with Normal Probability Functions

v0.2.1 · Mar 17, 2019 · GPL (>= 3)

Description

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: <https://www.coursera.org/learn/machine-learning/lecture/C8IJp/algorithm/>, and is also described in: Aleksandar Lazarevic, Levent Ertoz, Vipin Kumar, Aysel Ozgur, Jaideep Srivastava (2003) <doi:10.1137/1.9781611972733.3>.

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LazyData

'LazyData' is specified without a 'data' directory
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LazyData

'LazyData' is specified without a 'data' directory

Check History

NOTE 11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
NOTE r-oldrel-macos-arm64

LazyData

'LazyData' is specified without a 'data' directory
NOTE r-oldrel-macos-x86_64

LazyData

'LazyData' is specified without a 'data' directory
NOTE r-oldrel-windows-x86_64

LazyData

'LazyData' is specified without a 'data' directory

Version History

new 0.2.1 Mar 10, 2026
updated 0.2.1 ← 0.2.0 diff Mar 17, 2019
updated 0.2.0 ← 0.1.0 diff Apr 7, 2018
new 0.1.0 Feb 21, 2018