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1.7 KiB
1.7 KiB
Sebastian Raschka, 2015
Python Machine Learning - Supplementary Datasets
Wine Dataset
- Used in chapters 4 and 5
The Wine dataset for classification.
| Samples | 178 |
| Features | 13 |
| Classes | 3 |
| Data Set Characteristics: | Multivariate |
| Attribute Characteristics: | Integer, Real |
| Associated Tasks: | Classification |
| Missing Values | None |
| column | attribute |
|---|---|
| 1) | Class Label |
| 2) | Alcohol |
| 3) | Malic acid |
| 4) | Ash |
| 5) | Alcalinity of ash |
| 6) | Magnesium |
| 7) | Total phenols |
| 8) | Flavanoids |
| 9) | Nonflavanoid phenols |
| 10) | Proanthocyanins |
| 11) | intensity |
| 12) | Hue |
| 13) | OD280/OD315 of diluted wines |
| 14) | Proline |
| class | samples |
|---|---|
| 0 | 59 |
| 1 | 71 |
| 2 | 48 |
References
- Forina, M. et al, PARVUS - An Extendible Package for Data Exploration, Classification and Correlation. Institute of Pharmaceutical and Food Analysis and Technologies, Via Brigata Salerno, 16147 Genoa, Italy.
- Source: https://archive.ics.uci.edu/ml/datasets/Wine
- Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository. Irvine, CA: University of California, School of Information and Computer Science.