Package: amelie 0.2.1

amelie: Anomaly Detection with Normal Probability Functions

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>.

Authors:Dmitriy Bolotov [aut, cre]

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NEWS

# Install 'amelie' in R:
install.packages('amelie', repos = c('https://dbolotov.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/dbolotov/amelie/issues

On CRAN:

Conda:

anomaly-detection

3.70 score 6 scripts 285 downloads 1 mentions 2 exports 0 dependencies

Last updated 6 years agofrom:82d3d7bdc6. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 15 2025
R-4.5-winOKFeb 15 2025
R-4.5-macOKFeb 15 2025
R-4.5-linuxOKFeb 15 2025
R-4.4-winOKFeb 15 2025
R-4.4-macOKFeb 15 2025
R-4.3-winOKFeb 15 2025
R-4.3-macOKFeb 15 2025

Exports:adpdfunc

Dependencies:

Amelie Introduction

Rendered fromamelie-introduction.Rmdusingknitr::rmarkdownon Feb 15 2025.

Last update: 2018-03-23
Started: 2018-02-19