themis

Extra Recipes Steps for Dealing with Unbalanced Data

Last update: 14 August 2023

Copyright license: MIT license, File License

Software version identifier: 1.0.1, 0.1.0, 0.1.1, 0.1.2, 0.1.3, 0.1.4, 0.2.0, 0.2.1, 0.2.2, 1.0.0, 1.0.1, 1.0.2

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>.