dbolotov/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>.

Getting started

Package details

Maintainer
LicenseGPL (>= 3)
Version0.3.0.9000
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("dbolotov/amelie")
dbolotov/amelie documentation built on April 14, 2018, 2:56 a.m.