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outliertree (version 1.9.0)

Explainable Outlier Detection Through Decision Tree Conditioning

Description

Outlier detection method that flags suspicious values within observations, constrasting them against the normal values in a user-readable format, potentially describing conditions within the data that make a given outlier more rare. Full procedure is described in Cortes (2020) . Loosely based on the 'GritBot' software.

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Install

install.packages('outliertree')

Monthly Downloads

562

Version

1.9.0

License

GPL (>= 3)

Issues

2

Pull Requests

0

Stars

64

Forks

4

Maintainer

David Cortes

Last Published

February 9th, 2024

Functions in outliertree (1.9.0)

[.outlieroutputs

Slice or sub-set outliers
predict.outliertree

Predict method for Outlier Tree
extract.training.outliers

Extract outliers found in training data
outlier.tree

Outlier Tree
variable.names.outliertree

Get Variable Names for OutlierTree Model
summary.outlieroutputs

Print outliers in human-readable format
print.outlieroutputs

Print outliers in human-readable format
as.list.outlieroutputs

Convert outlier outputs to R list
print.outliertree

Print summary information from Outlier Tree model
check.outlierness.bounds

Check values that could potentially flag an observation as outlier
summary.outliertree

Print summary information from Outlier Tree model
titanic

Data about passengers of the RMS Titanic
hypothyroid

Data about thyroid hormones for anonymous patients