The data analyzed in this chapter is the Wine dataset found in the UC-Irvine Machine Learning repository. The data 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 chemical components found in each of the three types of wine. There are 59, 71, and 48 instances respectively in the three classes. The class codes are 1, 2, and 3.
The attributes are as follows:
- Alcohol
- Malic acid
- Ash
- Alcalinity of ash
- Magnesium
- Total phenols
- Flavanoids
- Nonflavanoid phenols
- Proanthocyanins
- Color intensity
- Hue
- OD280/OD315 of diluted wines
- Proline
In the context of classification, the task is to use the 13 attributes to classify each observation into one of the three wine types. Note that all 13 attributes are numeric.
