deviance_normal

actual

predicted

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

Weighted average of (unscaled) unit normal deviance. This equals the weighted mean-squared error, see e.g. the reference below. The smaller the deviance, 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

deviance_normal 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>...</dt>
<dd>Further arguments passed to <code>mse</code>.</dd></dl>

Arguments

Normal Deviance — deviance_normal

<dl>

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


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


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


<dt>...</dt>
<dd>Further arguments passed to <code>mse</code>.</dd>

</dl>

deviance_normal: Normal Deviance

Description

Usage

Value

Arguments

References

See Also

Examples