Context Wine recognition dataset from UC Irvine. Great for testing out different classifiers **Labels:** "name" - Number denoting a specific wine class Number of instances of each wine class - Class 1 - 59 - Class 2 - 71 - Class 3 - 48 **Features:** 1. Alcohol 2. Malic acid 3. Ash 4. Alcalinity of ash 5. Magnesium 6. Total phenols 7. Flavanoids 8. Nonflavanoid phenols 9. Proanthocyanins 10. Color intensity 11. Hue 12. OD280/OD315 of diluted wines 13. Proline Content "This data set is the result of a chemical analysis of wines grown in the same region in Italy but derived from three different cultivars. The analysis determined the quantities of 13 constituents found in each of the three types of wines" Acknowledgements Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science. @misc{Lichman:2013 , author = "M. Lichman