mape

Strictly positive observed values.

actual

predicted

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

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

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>

mape: Mean Absolute Percentage Error

Description

Usage

Value

Arguments

Examples