medae

Calculates weighted median absolute error of predicted values.
The smaller the value, 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

medae 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>weighted_median()</code>.</dd></dl>

Arguments

Median Absolute Error — medae

<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>weighted_median()</code>.</dd>

</dl>

medae: Median Absolute Error

Description

Usage

Value

Arguments

Examples