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.


Reference manual

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1.7.4 by David Cortes, a month ago


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