This dataset is 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: http://www3.dsi.uminho.pt/pcortez/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.).
wine_quality
A data frame with 6497 observations on the following 13 variables.
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)
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. '@'2009
These datasets can be viewed as classification or regression tasks. The classes are ordered and not balanced (e.g. there are munch 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.
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.
https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/
https://archive.ics.uci.edu/ml/datasets/Wine+Quality
http://www3.dsi.uminho.pt/pcortez/wine/