Datasets:
Tasks:
Tabular Classification
Modalities:
Tabular
Formats:
csv
Sub-tasks:
tabular-multi-class-classification
Size:
n<1K
Tags:
License:
| annotations_creators: | |
| - no-annotation | |
| language: [] | |
| language_creators: | |
| - expert-generated | |
| license: | |
| - unknown | |
| pretty_name: Wine Recognition Dataset | |
| size_categories: | |
| - n<1K | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - tabular-classification | |
| task_ids: | |
| - tabular-multi-class-classification | |
| # Dataset Card for Wine Recognition dataset | |
| ## Dataset Description | |
| - **Homepage:** https://archive.ics.uci.edu/ml/datasets/wine | |
| - **Papers:** | |
| 1. S. Aeberhard, D. Coomans and O. de Vel, | |
| Comparison of Classifiers in High Dimensional Settings, | |
| Tech. Rep. no. 92-02, (1992), Dept. of Computer Science and Dept. of | |
| Mathematics and Statistics, James Cook University of North Queensland. | |
| 2. S. Aeberhard, D. Coomans and O. de Vel, | |
| "THE CLASSIFICATION PERFORMANCE OF RDA" | |
| Tech. Rep. no. 92-01, (1992), Dept. of Computer Science and Dept. of | |
| Mathematics and Statistics, James Cook University of North Queensland. | |
| - **Point of Contact:** stefan'@'coral.cs.jcu.edu.au | |
| ### Dataset Summary | |
| These data are the results 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. In a classification context, this is a well posed problem with "well behaved" class structures. A good data set for first testing of a new classifier, but not very challenging. | |
| ### Supported Tasks and Leaderboards | |
| Classification (cultivar) from continuous variables (all other variables) | |
| ## Dataset Structure | |
| ### Data Instances | |
| 178 wines | |
| ### Data Fields | |
| 1. Wine category (cultivar) | |
| 2. Alcohol | |
| 3. Malic acid | |
| 4. Ash | |
| 5. Alcalinity of ash | |
| 6. Magnesium | |
| 7. Total phenols | |
| 8. Flavanoids | |
| 9. Nonflavanoid phenols | |
| 10. Proanthocyanins | |
| 11. Color intensity | |
| 12. Hue | |
| 13. OD280/OD315 of diluted wines | |
| 14. Proline | |
| ### Data Splits | |
| None | |
| ## Dataset Creation | |
| ### Source Data | |
| https://archive.ics.uci.edu/ml/datasets/wine | |
| #### Initial Data Collection and Normalization | |
| Original Owners: | |
| 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. | |
| ## Additional Information | |
| ### Dataset Curators | |
| Stefan Aeberhard | |
| ### Licensing Information | |
| No information found on the original website |