Data
red_wine

red_wine

active ARFF CC BY 4.0 Visibility: public Uploaded 22-12-2022 by Sebastian Fischer
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Data Description The data were collected from May/2004 to February/2007 using only protected designation of origin samples that were tested at the official certification entity (CVRVV). The CVRVV is an inter-professional organization with the goal of improving the quality and marketing of vinho verde. The data were recorded by a computerized system (iLab), which automatically manages the process of wine sample testing from producer requests to laboratory and sensory analysis. Each entry denotes a given test (analytical or sensory). This dataset contains only the read wine. The goal is using chemical analysis determine the quality of the wine. Attribute Description 1. *fixed_acidity* 2. *volatile_acidity* 3. *citric_acid* 4. *residual_sugar* 5. *chlorides* 6. *free_sulfur_dioxide* 7. *total_sulfur_dioxide* 8. *density* 9. *pH* 10. *sulphates* 11. *alcohol* 12. *quality* - target feature

12 features

quality (target)numeric6 unique values
0 missing
fixed_aciditynumeric96 unique values
0 missing
volatile_aciditynumeric143 unique values
0 missing
citric_acidnumeric80 unique values
0 missing
residual_sugarnumeric91 unique values
0 missing
chloridesnumeric153 unique values
0 missing
free_sulfur_dioxidenumeric60 unique values
0 missing
total_sulfur_dioxidenumeric144 unique values
0 missing
densitynumeric436 unique values
0 missing
pHnumeric89 unique values
0 missing
sulphatesnumeric96 unique values
0 missing
alcoholnumeric65 unique values
0 missing

19 properties

1599
Number of instances (rows) of the dataset.
12
Number of attributes (columns) of the dataset.
0
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.
12
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0.28
Average class difference between consecutive instances.
0
Percentage of missing values.
0.01
Number of attributes divided by the number of instances.
100
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

1 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: quality
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