r_squared_poisson

Wrapper to <code>r_squared</code> with <code>deviance_function = deviance_poisson</code>.

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

r_squared_poisson function

<dl><dt>actual</dt>
<dd>Observed values.</dd>
<dt>predicted</dt>
<dd>Predicted values.</dd>
<dt>w</dt>
<dd>Optional case weights.</dd>
<dt>reference_mean</dt>
<dd>An optional reference mean used to derive the null deviance.
Recommended in out-of-sample applications.</dd>
<dt>...</dt>
<dd>Further arguments passed to <code>r_squared()</code>.</dd></dl>

Arguments

Pseudo R-Squared regarding Poisson deviance — r_squared_poisson

<dl>

<dt>actual</dt>
<dd>Observed values.</dd>


<dt>predicted</dt>
<dd>Predicted values.</dd>


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


<dt>reference_mean</dt>
<dd>An optional reference mean used to derive the null deviance.
Recommended in out-of-sample applications.</dd>


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

</dl>

r_squared_poisson: Pseudo R-Squared regarding Poisson deviance

Description

Usage

Value

Arguments

Details

See Also

Examples