deviance_bernoulli

actual

Predicted values strictly between 0 and 1.

predicted

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

Calculates weighted average of unit Bernoulli deviance. Defined as twice logLoss. 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_bernoulli function

<dl><dt>actual</dt>
<dd>Observed values (0 or 1).</dd>
<dt>predicted</dt>
<dd>Predicted values strictly between 0 and 1.</dd>
<dt>w</dt>
<dd>Optional case weights.</dd>
<dt>...</dt>
<dd>Further arguments passed to <code>logLoss</code>.</dd></dl>

Arguments

Bernoulli Deviance — deviance_bernoulli

<dl>

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


<dt>predicted</dt>
<dd>Predicted values strictly between 0 and 1.</dd>


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


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

</dl>

deviance_bernoulli: Bernoulli Deviance

Description

Usage

Value

Arguments

See Also

Examples