themis
Extra Recipes Steps for Dealing with Unbalanced Data
A dataset with an uneven number of cases in each class is said to be unbalanced. Many models produce a subpar performance on unbalanced datasets. A dataset can be balanced by increasing the number of minority cases using SMOTE 2011 doi:10.48550/arXiv.1106.1813, BorderlineSMOTE 2005 doi:10.1007/11538059_91 and ADASYN 2008 https://ieeexplore.ieee.org/document/4633969. Or by decreasing the number of majority cases using NearMiss 2003 https://www.site.uottawa.ca/~nat/Workshop2003/jzhang.pdf or Tomek link removal 1976 https://ieeexplore.ieee.org/document/4309452.
- Version1.0.3
- R versionR (≥ 3.6)
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- Last release01/23/2025
Documentation
Team
Emil Hvitfeldt
MaintainerShow author detailsPosit Software, PBC
Insights
Last 30 days
This package has been downloaded 12,293 times in the last 30 days. The downloads are officially high enough to crash an underfunded departmental server. Quite an accomplishment! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 353 times.
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Last 365 days
This package has been downloaded 89,318 times in the last 365 days. An impressive feat! Enough downloads to make even seasoned academics take note. The day with the most downloads was Apr 09, 2025 with 879 downloads.
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Dependencies
- Depends1 package
- Imports14 packages
- Suggests5 packages
- Reverse Imports1 package
- Reverse Suggests3 packages