Hands-On Artificial Intelligence for IoT

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Wine quality dataset

Wineries around the world have to undergo wine certifications and quality assessments to safeguard human health. The wine certification is performed with the help of physicochemical analysis and sensory tests. With the advancement of technology, the physicochemical analysis can be performed routinely via in-vitro equipment.

We use this dataset for classification examples in this book. The dataset can be downloaded from the UCI-ML repository (https://archive.ics.uci.edu/ml/datasets/Wine+Quality). The wine quality dataset contains results of physicochemical tests on different samples of red and white wine. Each sample was further rated by an expert wine taster for quality on a scale of 0—10.

The dataset contains in total 4,898 instances; it has a total of 12 attributes. The 12 attributes are as follows:

Fixed acidity
Volatile acidity
Citric acid
Residual sugar
Chlorides
Free sulfur dioxide
Total sulfur dioxide
Density
pH
Sulfates
Alcohol
Quality

The dataset is available in the CSV format.

Details about the dataset can be read from this paper: Cortez, Paulo, et al. Modeling wine preferences by data mining from physicochemical properties. Decision Support Systems 47.4 (2009): 547-553 ( https://repositorium.sdum.uminho.pt/bitstream/1822/10029/1/wine5.pdf).