Multiclass classification with the Wine dataset
The Wine dataset is another classic and simple dataset hosted in the UCI machine learning repository. It contains chemical analysis of the content of wines grown in the same region in Italy, but derived from three different cultivars. It is used to determine models for classification problems by predicting the source (cultivar) of wine as class or target variable. The dataset has the following 13 features (dependent variables), which are all numeric:
- Alcohol
- Malic acid
- Ash
- Alcalinity of ash
- Magnesium
- Total phenols
- Flavanoids
- Nonflavanoid phenols
- Proanthocyanins
- Color intensity
- Hue
- OD280/OD315 of diluted wines
- Proline
The examples or instances are classified into three classes: 1, 2 and 3.
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