smape

yTest

yHat


This criterion is frequently used in business forecasting.
See Wikipedia article
<a href="https://en.wikipedia.org/wiki/Symmetric_mean_absolute_percentage_error">https://en.wikipedia.org/wiki/Symmetric_mean_absolute_percentage_error</a>.


 regression

 models

Engines for cross-validation of many types of regression and class prediction models are provided. These engines include built-in support for 'glmnet', 'lars', 'plus', 'MASS', 'rpart', 'C50' and 'randomforest'. It is easy for the user to add other regression or classification algorithms. The 'parallel' package is used to improve speed. Several data generation algorithms for problems in regression and classification are provided.

smape: Mean Absolute Percentage Error

Description

Usage

Arguments

Value

Details

See Also

Examples