4. Conclusions and implications
In recent years, the interest in wine has increased, leading to
growth of the wine industry. As a consequence, companies are
investing in newtechnologies to improve wine production and selling.
Quality certification is a crucial step for both processes and is currently
largely dependent on wine tasting by human experts. This work aims
at the prediction of wine preferences from objective analytical tests
that are available at the certification step. A large dataset (with 4898
white and 1599 red entries) was considered, including vinho verde
samples from the northwest region of Portugal. This case study was
addressed by two regression tasks, where each wine type preference
is modeled in a continuous scale, from 0 (very bad) to 10 (excellent).
This approach preserves the order of the classes, allowing the
evaluation of distinct accuracies, according to the degree of error
tolerance (T) that is accepted.
Due to advances in the data