wine: Wine quality

In bgreenwell/treemisc: Data Sets and Functions to Accompany "Tree-Based Methods for Statistical Learning in R"

Wine quality

Description

These data are related to red and white variants of the Portuguese "Vinho Verde" wine. For details, see 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 data can be used for 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, it is not known if all input variables are relevant. So it could be interesting to test feature selection methods.

Format

A data frame with 6497 rows and 13 variables.

Details

fixed.acidity

Input feature (continuous).

volatile.acidity

Input feature (continuous).

citric.acid

Input feature (continuous).

residual.sugar

Input feature (continuous).

chlorides

Input feature (continuous).

free.sulfur.dioxide

Input feature (continuous).

total.sulfur.dioxide

Input feature (continuous).

density

Input feature (continuous).

pH

Input feature (continuous).

sulphates

Input feature (continuous).

alcohol

Input feature (continuous).

quality

Target variable (continuous).

type

Input feature specifying whether it's a red or white wine (factor).

Source

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

bgreenwell/treemisc documentation built on Oct. 26, 2022, 12:56 a.m.