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bagged.outliertrees  

Robust Explainable Outlier Detection Based on OutlierTree
View on CRAN: Click here


Download and install bagged.outliertrees package within the R console
Install from CRAN:
install.packages("bagged.outliertrees")

Install from Github:
library("remotes")
install_github("cran/bagged.outliertrees")

Install by package version:
library("remotes")
install_version("bagged.outliertrees", "1.0.0")



Attach the package and use:
library("bagged.outliertrees")
Maintained by
Rafael Santos
[Scholar Profile | Author Map]
First Published: 2021-07-06
Latest Update: 2021-07-06
Description:
Bagged OutlierTrees is an explainable unsupervised outlier detection method based on an ensemble implementation of the existing OutlierTree procedure (Cortes, 2020). This implementation takes advantage of bootstrap aggregating (bagging) to improve robustness by reducing the possible masking effect and subsequent high variance (similarly to Isolation Forest), hence the name "Bagged OutlierTrees". To learn more about the base procedure OutlierTree (Cortes, 2020), please refer to .
How to cite:
Rafael Santos (2021). bagged.outliertrees: Robust Explainable Outlier Detection Based on OutlierTree. R package version 1.0.0, https://cran.r-project.org/web/packages/bagged.outliertrees. Accessed 10 May. 2025.
Previous versions and publish date:
No previous versions
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Complete documentation for bagged.outliertrees
Functions, R codes and Examples using the bagged.outliertrees R package
Some associated functions: bagged.outliertrees . hypothyroid . predict.bagged.outliertrees . print.bagged.outlieroutputs . 
Some associated R codes: bagged.outliertrees.R . data.R . predict.bagged.outliertrees.R . print.bagged.outlieroutputs.R .  Full bagged.outliertrees package functions and examples
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