wine.quality {SLmetrics} | R Documentation |
Wine quality dataset
Description
This dataset contains measurements of various chemical properties of white wines along with their quality ratings and a quality classification. The dataset was obtained from the UCI Machine Learning Repository.
The data is provided as a list with two components:
- features
A data frame containing the chemical properties of the wines. The variables include:
- fixed_acidity
Fixed acidity (g/L).
- volatile_acidity
Volatile acidity (g/L), mainly due to acetic acid.
- citric_acid
Citric acid (g/L).
- residual_sugar
Residual sugar (g/L).
- chlorides
Chloride concentration (g/L).
- free_sulfur_dioxide
Free sulfur dioxide (mg/L).
- total_sulfur_dioxide
Total sulfur dioxide (mg/L).
- density
Density of the wine (g/cm
^3
).- pH
pH value of the wine.
- sulphates
Sulphates (g/L).
- alcohol
Alcohol content (% by volume).
- target
A list containing two elements:
- regression
A numeric vector representing the wine quality scores (used as the regression target).
- class
A factor with levels
"High Quality"
,"Medium Quality"
, and"Low Quality"
, where classification is determined as follows:- High Quality
quality
\geq
7.- Low Quality
quality
\leq
4.- Medium Quality
for all other quality scores.
Usage
data(wine.quality)
Format
A list with two components:
- features
A data frame with 11 chemical property variables.
- target
A list with two elements:
regression
(wine quality scores) andclass
(quality classification).
References
Cortez, Paulo, et al. "Modeling wine preferences by data mining from physicochemical properties." Decision support systems 47.4 (2009): 547-553.