tunable.step_adasyn

tunable.step_bsmote

tunable.step_downsample

tunable.step_nearmiss

tunable.step_rose

tunable.step_smote

tunable.step_smotenc

tunable_themis

tunable.step_upsample

These functions define what parameters can be tuned for specific steps.
They also define the recommended objects from the <code>dials</code> package that can
be used to generate new parameter values and other characteristics.

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>.

Emil Hvitfeldt

themis

Extra Recipes Steps for Dealing with Unbalanced Data

Posit Software, PBC 

tunable.step_adasyn function

<dl><dt>x</dt>
<dd>A recipe step object</dd>
<dt>...</dt>
<dd>Not used.</dd></dl>

Arguments

tunable methods for themis — tunable.step_adasyn

<dl>

<dt>x</dt>
<dd>A recipe step object</dd>


<dt>...</dt>
<dd>Not used.</dd>

</dl>

tunable methods for themis

tunable.step_adasyn: tunable methods for themis

Description

Usage

Value

Arguments