
Wine
Donated on 7/1/1991
Using chemical analysis determine the origin of wines
Dataset Characteristics
Multivariate
Subject Area
Physical
Associated Tasks
Classification
Attribute Type
Integer, Real
# Instances
178
# Attributes
13
Information
For what purpose was the dataset created?
test
Additional Information
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. I think that the initial data set had around 30 variables, but for some reason I only have the 13 dimensional version. I had a list of what the 30 or so variables were, but a.) I lost it, and b.), I would not know which 13 variables are included in the set. The attributes are (dontated by Riccardo Leardi, riclea@anchem.unige.it ) 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 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.
Has Missing Values
Symbol: 0
Attribute Information
Additional Information
All attributes are continuous No statistics available, but suggest to standardise variables for certain uses (e.g. for us with classifiers which are NOT scale invariant) NOTE: 1st attribute is class identifier (1-3)
Features
Attribute Name | Role | Type | Description | Units | Missing Values |
---|---|---|---|---|---|
class | Target | Categorical | false | ||
Alcohol | Feature | Continuous | false | ||
Malicacid | Feature | Continuous | false | ||
Ash | Feature | Continuous | false | ||
Alcalinity_of_ash | Feature | Continuous | false | ||
Magnesium | Feature | Continuous | false | ||
Total_phenols | Feature | Continuous | false | ||
Flavanoids | Feature | Continuous | false | ||
Nonflavanoid_phenols | Feature | Continuous | false | ||
Proanthocyanins | Feature | Continuous | false |
0 to 10 of 14
Baseline Model Performance
Papers Citing this Dataset
By Shinpei Imori, Hidetoshi Shimodaira. 2019
Published in Entropy.
By Hongkang Yang, Esteban Tabak. 2019
Published in
By Takanori Fujiwara, Oh-Hyun Kwon, Kwan-Liu Ma. 2019
Published in ArXiv.
0 to 5 of 130
Aeberhard,Stefan and Forina,M.. (1991). Wine. UCI Machine Learning Repository. https://doi.org/10.24432/C5PC7J.
@misc{misc_wine_109, author = {Aeberhard,Stefan and Forina,M.}, title = {{Wine}}, year = {1991}, howpublished = {UCI Machine Learning Repository}, note = {{DOI}: https://doi.org/10.24432/C5PC7J} }
Creators
Stefan Aeberhard
M. Forina
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.