OpenML
wine

wine

active ARFF See source Visibility: public Uploaded 16-06-2022 by Leo Grin
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Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark. Original source: https://archive.ics.uci.edu/ml/datasets/wine+quality Please give credit to the original source if you use this dataset.

12 features

quality (target)nominal2 unique values
0 missing
fixed aciditynumeric94 unique values
0 missing
volatile aciditynumeric145 unique values
0 missing
citric acidnumeric83 unique values
0 missing
residual sugarnumeric249 unique values
0 missing
chloridesnumeric142 unique values
0 missing
free sulfur dioxidenumeric105 unique values
0 missing
total sulfur dioxidenumeric248 unique values
0 missing
densitynumeric722 unique values
0 missing
pHnumeric96 unique values
0 missing
sulphatesnumeric94 unique values
0 missing
alcoholnumeric81 unique values
0 missing

19 properties

2554
Number of instances (rows) of the dataset.
12
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
11
Number of numeric attributes.
1
Number of nominal attributes.
8.33
Percentage of binary attributes.
0
Percentage of instances having missing values.
1
Average class difference between consecutive instances.
0
Percentage of missing values.
0
Number of attributes divided by the number of instances.
91.67
Percentage of numeric attributes.
50
Percentage of instances belonging to the most frequent class.
8.33
Percentage of nominal attributes.
1277
Number of instances belonging to the most frequent class.
50
Percentage of instances belonging to the least frequent class.
1277
Number of instances belonging to the least frequent class.
1
Number of binary attributes.

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