shown in this study, high accuracies were achieved for this tolerance. The model
could also be used to improve the training of oenology students. Furthermore,
the relative importance of the inputs brought interesting insights regarding the
impact of the analytical tests. Since some variables can be controlled in the
production process this information can be used to improve the wine quality. For
instance, alcohol concentration can be increased or decreased by monitoring the
grape sugar concentration prior to the harvest. Also, the residual sugar in wine
could be raised by suspending the sugar fermentation carried out by yeasts. In
future work, we intend to model preferences from niche and/or profitable markets
(e.g. for a particular country by providing free wine tastings at supermarkets),
aiming at the design of brands that match these market needs. We will also test
other DM algorithms that specifically build rankers, such as regression trees