DESCRIPTION

Package: isofor
Type: Package
Title: Isolation Forest Anomaly Detection
Version: 1.0.0
Author: Eric Graves [aut, cre]
    Ignat Drozdov [ctb]
Maintainer: Eric Graves <gravcon5@gmail.com>
Description: Implementation of the Isolation forest method from the paper "Isolation based Anomaly Detection" (Liu, Ting and Zhou <doi:10.1145/2133360.2133363>).
    An isolation forest measures how easy it is to isolate multivariate observations.
    Observations that can be isolated with fewer axis-aligned partitions from random
    decision trees are more likely to be anomalous.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Collate: 
    'util.R'
    'IsolationForest.R'
    'RcppExports.R'
    'predict.R'
LinkingTo: Rcpp
Imports:
    Rcpp,
    Matrix,
    parallel
Suggests:
    shiny