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:
amelie_0.2.1.tar.gz
amelie_0.2.1.zip(r-4.5)amelie_0.2.1.zip(r-4.4)amelie_0.2.1.zip(r-4.3)
amelie_0.2.1.tgz(r-4.4-any)amelie_0.2.1.tgz(r-4.3-any)
amelie_0.2.1.tar.gz(r-4.5-noble)amelie_0.2.1.tar.gz(r-4.4-noble)
amelie_0.2.1.tgz(r-4.4-emscripten)amelie_0.2.1.tgz(r-4.3-emscripten)
amelie.pdf |amelie.html✨
amelie/json (API)
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
Last updated 6 years agofrom:82d3d7bdc6. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 17 2024 |
| R-4.5-win | OK | Nov 17 2024 |
| R-4.5-linux | OK | Nov 17 2024 |
| R-4.4-win | OK | Nov 17 2024 |
| R-4.4-mac | OK | Nov 17 2024 |
| R-4.3-win | OK | Nov 17 2024 |
| R-4.3-mac | OK | Nov 17 2024 |
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| ad: anomaly detection with normal probability density functions. | ad ad.default ad.formula print.ad |
| amelie: A package for anomaly detection. | amelie-package amelie |
| Compute the probability density function of a matrix of features. | pdfunc |
| Predict method for ad Objects | predict.ad |
