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>.
Version: 0.2.1 Imports: stats Suggests: testthat, knitr, rmarkdown Published: 2019-03-18 DOI: 10.32614/CRAN.package.amelie Author: Dmitriy Bolotov [aut, cre] Maintainer: Dmitriy Bolotov <dbolotov at live.com> License: GPL (≥ 3) NeedsCompilation: no Materials: NEWS CRAN checks: amelie results Documentation: Reference manual: amelie.pdf Vignettes: IntroductionPlease use the canonical form https://CRAN.R-project.org/package=amelie to link to this page.
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