Wine Quality Dataset

Dataset Overview
Data Type Multivariate Default Task Classification, Regression
Attribute Type Real Published Year 2009
Area of Dataset Business Missing Values No
No. of Instances 4898 No. of Attribute 12

Dataset Description:

The dataset contains different chemical information about wine. It has 4898 instances with 14 variables each. The dataset is good for classification and regression tasks. The model can be used to predict wine quality.

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.

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