Explainable Outlier Detection Through Decision Tree Conditioning

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' < https://www.rulequest.com/gritbot-info.html> software.


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install.packages("outliertree")

1.7.4 by David Cortes, a month ago


https://github.com/david-cortes/outliertree


Report a bug at https://github.com/david-cortes/outliertree/issues


Browse source code at https://github.com/cran/outliertree


Authors: David Cortes


Documentation:   PDF Manual  


GPL (>= 3) license


Imports Rcpp

Suggests knitr, rmarkdown

Linking to Rcpp, Rcereal


Imported by bagged.outliertrees.

Suggested by isotree.


See at CRAN