Wine Quality

Donated on 10/6/2009

Two datasets are included, related to red and white vinho verde wine samples, from the north of Portugal. The goal is to model wine quality based on physicochemical tests (see [Cortez et al., 2009], http://www3.dsi.uminho.pt/pcortez/wine/).

Dataset Characteristics

Multivariate

Subject Area

Business

Associated Tasks

Classification, Regression

Feature Type

Real

# Instances

4898

# Features

11

Dataset Information

Additional Information

The two datasets are related to red and white variants of the Portuguese "Vinho Verde" wine. For more details, consult: http://www.vinhoverde.pt/en/ or the reference [Cortez et al., 2009]. Due to privacy and logistic issues, only physicochemical (inputs) and sensory (the output) variables are available (e.g. there is no data about grape types, wine brand, wine selling price, etc.). These datasets can be viewed as classification or regression tasks. The classes are ordered and not balanced (e.g. there are many more normal wines than excellent or poor ones). Outlier detection algorithms could be used to detect the few excellent or poor wines. Also, we are not sure if all input variables are relevant. So it could be interesting to test feature selection methods.

Has Missing Values?

No

Introductory Paper

Modeling wine preferences by data mining from physicochemical properties

By P. Cortez, A. Cerdeira, Fernando Almeida, Telmo Matos, J. Reis. 2009

Published in Decision Support Systems

Variables Table

Variable NameRoleTypeDemographicDescriptionUnitsMissing Values
fixed_acidityFeatureContinuousno
volatile_acidityFeatureContinuousno
citric_acidFeatureContinuousno
residual_sugarFeatureContinuousno
chloridesFeatureContinuousno
free_sulfur_dioxideFeatureContinuousno
total_sulfur_dioxideFeatureContinuousno
densityFeatureContinuousno
pHFeatureContinuousno
sulphatesFeatureContinuousno

0 to 10 of 13

Additional Variable Information

For more information, read [Cortez et al., 2009]. Input variables (based on physicochemical tests): 1 - fixed acidity 2 - volatile acidity 3 - citric acid 4 - residual sugar 5 - chlorides 6 - free sulfur dioxide 7 - total sulfur dioxide 8 - density 9 - pH 10 - sulphates 11 - alcohol Output variable (based on sensory data): 12 - quality (score between 0 and 10)

Reviews

There are no reviews for this dataset yet.

Login to Write a Review
Download
1 citations
260794 views

Keywords

Chemistry

Creators

Paulo Cortez

A. Cerdeira

F. Almeida

T. Matos

J. Reis

License

By using the UCI Machine Learning Repository, you acknowledge and accept the cookies and privacy practices used by the UCI Machine Learning Repository.

Read Policy