The inputs include objective tests (e.g. PH values) and the output is based on sensory data (median of at least 3 evaluations made by wine experts) of white wine. Each expert graded the wine quality between 0 (very bad) and 10 (very excellent).


Cortez, P., Cerdeira, A., Almeida, F., Matos T. and Reis, J. (2009). Modeling wine preferences by data mining from physicochemical properties. In Decision Support Systems, Elsevier, 47(4):547-553.


## load wine and convert to a multiclass problem
data(wine, package = "randomForestSRC")
wine$quality <- factor(wine$quality)