ravi3222/classification_with_wine_dataset

Muticlass classification problem to classify customer segments by different chemical properties of wine.

Classification_with_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:

The attributes are:

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

The examples or instances are classified into three classes: 1, 2 and 3.

You can find more about the dataset at http://archive.ics.uci.edu/ml/datasets/Wine.