mape

Calculates weighted mean absolute percentage error of predicted values.
The smaller, 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

mape function

<dl><dt>actual</dt>
<dd>Strictly positive 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_mean()</code>.</dd></dl>

Arguments

Mean Absolute Percentage Error — mape

<dl>

<dt>actual</dt>
<dd>Strictly positive 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_mean()</code>.</dd>

</dl>

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mape: Mean Absolute Percentage Error

Description

Usage

Value

Arguments

Examples