Package: outliertree 1.10.0-1
outliertree: 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) <doi:10.48550/arXiv.2001.00636>. Loosely based on the 'GritBot' <https://www.rulequest.com/gritbot-info.html> software.
Authors:
outliertree_1.10.0-1.tar.gz
outliertree_1.10.0-1.zip(r-4.7)outliertree_1.10.0-1.zip(r-4.6)outliertree_1.10.0-1.zip(r-4.5)
outliertree_1.10.0-1.tgz(r-4.6-x86_64)outliertree_1.10.0-1.tgz(r-4.6-arm64)outliertree_1.10.0-1.tgz(r-4.5-x86_64)outliertree_1.10.0-1.tgz(r-4.5-arm64)
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outliertree_1.10.0-1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
outliertree/json (API)
| # Install 'outliertree' in R: |
| install.packages('outliertree', repos = c('https://david-cortes.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/david-cortes/outliertree/issues
- hypothyroid - Data about thyroid hormones for anonymous patients
- titanic - Data about passengers of the RMS Titanic
anomaly-detectionoutlier-detectioncppopenmp
Last updated from:67ec1af6c1. Checks:13 OK. Indexed: yes.
A new build is currently in progress.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 148 | ||
| linux-devel-x86_64 | OK | 147 | ||
| source / vignettes | OK | 307 | ||
| linux-release-arm64 | OK | 143 | ||
| linux-release-x86_64 | OK | 138 | ||
| macos-release-arm64 | OK | 145 | ||
| macos-release-x86_64 | OK | 274 | ||
| macos-oldrel-arm64 | OK | 167 | ||
| macos-oldrel-x86_64 | OK | 274 | ||
| windows-devel | OK | 192 | ||
| windows-release | OK | 138 | ||
| windows-oldrel | OK | 127 | ||
| wasm-release | OK | 121 |
Exports:check.outlierness.boundsextract.training.outliersoutlier.tree
Explainable Outlier Detection in Titanic dataset
Rendered fromExplainable_Outlier_Detection_in_Titanic_dataset.Rmdusingknitr::rmarkdownon May 02 2026.Last update: 2022-02-17
Started: 2022-02-17
Introducing OutlierTree
Rendered fromIntroducing_OutlierTree.Rmdusingknitr::rmarkdownon May 02 2026.Last update: 2021-05-06
Started: 2021-05-06
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Slice or sub-set outliers | [.outlieroutputs |
| Convert outlier outputs to R list | as.list.outlieroutputs |
| Check values that could potentially flag an observation as outlier | check.outlierness.bounds |
| Extract outliers found in training data | extract.training.outliers |
| Data about thyroid hormones for anonymous patients | hypothyroid |
| Outlier Tree | outlier.tree |
| Predict method for Outlier Tree | predict.outliertree |
| Print outliers in human-readable format | print.outlieroutputs |
| Print summary information from Outlier Tree model | print.outliertree |
| Print outliers in human-readable format | summary.outlieroutputs |
| Print summary information from Outlier Tree model | summary.outliertree |
| Data about passengers of the RMS Titanic | titanic |
| Get Variable Names for OutlierTree Model | variable.names.outliertree |
