outliertree
Explainable Outlier Detection Through Decision Tree Conditioning
Outlier detection method that flags suspicious values within observations, contrasting 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.
- Version1.10.0
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- Last release09/06/2024
Documentation
Team
David Cortes
MaintainerShow author details
Insights
Last 30 days
This package has been downloaded 538 times in the last 30 days. More downloads than an obscure whitepaper, but not enough to bring down any servers. A solid effort! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 6,468 times in the last 365 days. A solid achievement! Enough downloads to get noticed at department meetings. The day with the most downloads was Sep 11, 2024 with 95 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Imports1 package
- Suggests4 packages
- Linking To2 packages
- Reverse Imports2 packages
- Reverse Suggests1 package