outForest

Multivariate Outlier Detection and Replacement

Provides a random forest based implementation of the method described in Chapter 7.1.2 (Regression model based anomaly detection) of Chandola et al. (2009) <doi.acm.org/10.1145/1541880.1541882>. It works as follows: Each numeric variable is regressed onto all other variables by a random forest. If the scaled absolute difference between observed value and out-of-bag prediction of the corresponding random forest is suspiciously large, then a value is considered an outlier. The package offers different options to replace such outliers, e.g. by realistic values found via predictive mean matching. Once the method is trained on a reference data, it can be applied to new data.

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Description file content

Type
Package
Package
outForest
Title
Multivariate Outlier Detection and Replacement
Version
0.1.0
Date
2020-01-09
Maintainer
Michael Mayer
Description
Provides a random forest based implementation of the method described in Chapter 7.1.2 (Regression model based anomaly detection) of Chandola et al. (2009) . It works as follows: Each numeric variable is regressed onto all other variables by a random forest. If the scaled absolute difference between observed value and out-of-bag prediction of the corresponding random forest is suspiciously large, then a value is considered an outlier. The package offers different options to replace such outliers, e.g. by realistic values found via predictive mean matching. Once the method is trained on a reference data, it can be applied to new data.
License
GPL (>= 2)
URL
BugReports
https://github.com/mayer79/outForest/issues
Depends
R (>= 3.5.0)
VignetteBuilder
knitr
Encoding
UTF-8
LazyData
true
Imports
stats, graphics, FNN, ranger, missRanger (>= 2.1.0)
Suggests
dplyr, knitr
RoxygenNote
7.0.2
NeedsCompilation
no
Packaged
2020-01-09 18:20:39 UTC; Michael
Author
Michael Mayer [aut, cre]
Repository
CRAN
Date/Publication
2020-01-13 15:50:03 UTC

install.packages('outForest')

0.1.0

11 days ago

https://github.com/mayer79/outForest

Michael Mayer

GPL (>= 2)

Depends on

R (>= 3.5.0)

Imports

stats, graphics, FNN, ranger, missRanger (>= 2.1.0)

Suggests

dplyr, knitr

Discussions