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outliertree

1.10.0-2Package record

Explainable Outlier Detection Through Decision Tree Conditioning

1packages dependsuggested by 1
15Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

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) doi:10.48550/arXiv.2001.00636. Loosely based on the 'GritBot' https://www.rulequest.com/gritbot-info.html software.

Install

Health

CRAN checks
13OK
Slowest check: 3.8 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK12 OK2026-04-25
Show 3 earlier changesHide 3 earlier changes
  • NOTE12 OK, 2 NOTE2026-04-22
  • ERROR11 OK, 2 NOTE, 1 ERROR2026-04-18
  • NOTE12 OK, 2 NOTE2026-03-10
Advisories

none known

Documentation

In release 1.10.0-2
README· In the repository, left out of the releaseVignettesYes · 2 · dynamicNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
13
Examples that run
100%3 run in a plain check
Exported functions with examples
33%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
8%

Downloads

15K
CRAN downloads in the past year
Rank #2,815 · ~41/day · ~1.2K/mo
Daily download trend is not available in this view yet.
1.9K30 days
5.3K90 days
15K1 year
Compare downloads with other packages →
Also on431 r2u5 autocran

Repository

64Stars
3Forks
2Open issues
0Open PRs
1Releases
223Commits
2Commit identities
outlier-detectionanomaly-detection
License file reads as GPL-3.0 · 223 commits · Last activity 2026-08-09 · 0% stars, 30d
Responsiveness
How these are sampled
PRs merged (all time)
100%
Median days to close, 50 most recently updated closed issues
1
Median days to close, 50 most recently updated closed PRs
0

Stars over time

2025-08-09 · 622026-07-07 · 64
PracticesBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/david-cortes/outliertree on 2026-10-22.

Git structural (1)
.gitattributes
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
7 external dependencies (excludes base and recommended)

Installing outliertree adds 2 packages (1 with compiled code, 2.1 MB of source tarballs). Heaviest: Rcpp 1.8 MB, Rcereal 261 KB.

Depends (1)
R >= 4.3.0
Imports (2)
Rcppmethods
LinkingTo (2)
Enhances (0)
none
Reverse dependencies
1direct
0indirect
Imports 1
Suggested by 1
Depends, Imports or LinkingTo, most downloaded first
Suggests, most downloaded first

Datasets

People & History

People (1)
Author, Maintainer since 1.0 (2019)
Releases (24)

Pick two releases to compare their code metrics.

Show 16 earlier eventsHide 16 earlier events

Package metadata

First published
2019-07-31
Total releases
24 / 7 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 4.3.0
Bundled data
75 KB / 2 files
Download size
618 KB
Appears in task views

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("outliertree")
Cortes, D. (2026). outliertree: Explainable Outlier Detection Through Decision Tree Conditioning (Version 1.10.0-2) [Computer software]. https://doi.org/10.32614/CRAN.package.outliertree

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for outliertree version 1.10.0-2 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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