gini_coefficient

actual

Predicted values of any value (not necessarly between 0 and 1).

predicted

Further arguments passed to <code>AUC</code>.

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, scoring
functions 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, Scoring Functions 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>

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gini_coefficient: Gini Coefficient

Description

Usage

Value

Arguments

See Also

Examples