odetector
Outlier Detection Using Partitioning Clustering Algorithms
An object is called "outlier" if it remarkably deviates from the other objects in a data set. Outlier detection is the process to find outliers by using the methods that are based on distance measures, clustering and spatial methods (Ben-Gal, 2005
- Version1.0.1
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- odetector citation info
- Last release11/08/2022
Documentation
Team
Zeynel Cebeci
Cagatay Cebeci
Show author detailsRolesContributorYalcin Tahtali
Insights
Last 30 days
This package has been downloaded 170 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 8 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 2,049 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Jan 25, 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.
Data provided by CRAN
Binaries
Dependencies
- Imports1 package
- Suggests3 packages