themis-package {themis} | R Documentation |
themis: Extra Recipes Steps for Dealing with Unbalanced Data
Description
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 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.
Author(s)
Maintainer: Emil Hvitfeldt emil.hvitfeldt@posit.co (ORCID)
Other contributors:
Posit Software, PBC [copyright holder, funder]
See Also
Useful links:
Report bugs at https://github.com/tidymodels/themis/issues