redWines {liver}

Red wines data set

Description

The redWines datasets are related to red variants of the Portuguese "Vinho Verde" wine. 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.).

The dataset 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.

Usage

 data( redWines ) 

Format

The redWines dataset, as a data frame, contains 1599 rows and 12 columns (variables/features). The 12 variables are:

Input variables (based on physicochemical tests):

• fixed acidity

• volatile acidity

• citric acid

• residual sugar

• chlorides

• free sulfur dioxide

• total sulfur dioxide

• density

• pH

• sulphates

• alcohol

  Output variable (based on sensory data)

• quality: score between 0 and 10.

Details

This dataset can be downloaded from the UCI machine learning repository:

https://archive.ics.uci.edu/dataset/186/wine+quality

References

Cortez, P., Cerdeira, A., Almeida, F., Matos, T., and Reis, J. (2009). Modeling wine preferences by data mining from physicochemical properties. Decision support systems, 47(4), 547-553.

See Also

whiteWines, adult, risk, churn, churnTel, bank, advertising, marketing, insurance, cereal, housePrice, house

Examples

data( redWines )

str( redWines )