themis

themis-package

<p>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 &lt;arXiv:1106.1813&gt;, BorderlineSMOTE and ADASYN. Or by 
    decreasing the number of majority cases using NearMiss or Tomek link 
    removal.</p>

internal

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>.

themis-package: themis: Extra Recipes Steps for Dealing with Unbalanced Data

Description

Arguments

See Also