gini_coefficient

Calculates weighted Gini coefficient, obtained as 2 * AUC - 1.
Up to ties in <code>predicted</code> equivalent to Somer's D.
The larger the Gini coefficient, the better.

Provides weighted versions of several metrics and performance
measures used in machine learning, including average unit deviances of
the Bernoulli, Tweedie, Poisson, and Gamma distributions, see
Jorgensen B. (1997, ISBN: 978-0412997112).  The package also contains
a weighted version of generalized R-squared, see e.g. Cohen, J. et al.
(2002, ISBN: 978-0805822236).  Furthermore, 'dplyr' chains are
supported.

Michael Mayer

MetricsWeighted

Weighted Metrics and Performance Measures for Machine Learning

Christian Lorentzen

gini_coefficient function

<dl><dt>actual</dt>
<dd>Observed values (0 or 1).</dd>
<dt>predicted</dt>
<dd>Predicted values of any value (not necessarly between 0 and 1).</dd>
<dt>w</dt>
<dd>Optional case weights.</dd>
<dt>...</dt>
<dd>Further arguments passed to <code>AUC()</code>.</dd></dl>

Arguments

Gini Coefficient — gini_coefficient

<dl>

<dt>actual</dt>
<dd>Observed values (0 or 1).</dd>


<dt>predicted</dt>
<dd>Predicted values of any value (not necessarly between 0 and 1).</dd>


<dt>w</dt>
<dd>Optional case weights.</dd>


<dt>...</dt>
<dd>Further arguments passed to <code>AUC()</code>.</dd>

</dl>

gini_coefficient: Gini Coefficient

Description

Usage

Value

Arguments

See Also

Examples