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Datasets:
katossky
/
wine-recognition

Tasks:
Tabular Classification
Sub-tasks:
tabular-multi-class-classification
Size Categories:
n<1K
Language Creators:
expert-generated
Annotations Creators:
no-annotation
Source Datasets:
original
Tags:
License:
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label
int64
1
3
alcohol
float64
11
14.8
malic acid
float64
0.74
5.8
ash
float64
1.36
3.23
alcalinity of ash
float64
10.6
30
magnesium
int64
70
162
total phenols
float64
0.98
3.88
flavanoids
float64
0.34
5.08
nonflavanoid phenols
float64
0.13
0.66
proanthocyanins
float64
0.41
3.58
color intensity
float64
1.28
13
hue
float64
0.48
1.71
OD280/OD315 of diluted wines
float64
1.27
4
proline
int64
278
1.68k
1
14.23
1.71
2.43
15.6
127
2.8
3.06
0.28
2.29
5.64
1.04
3.92
1,065
1
13.2
1.78
2.14
11.2
100
2.65
2.76
0.26
1.28
4.38
1.05
3.4
1,050
1
13.16
2.36
2.67
18.6
101
2.8
3.24
0.3
2.81
5.68
1.03
3.17
1,185
1
14.37
1.95
2.5
16.8
113
3.85
3.49
0.24
2.18
7.8
0.86
3.45
1,480
1
13.24
2.59
2.87
21
118
2.8
2.69
0.39
1.82
4.32
1.04
2.93
735
1
14.2
1.76
2.45
15.2
112
3.27
3.39
0.34
1.97
6.75
1.05
2.85
1,450
1
14.39
1.87
2.45
14.6
96
2.5
2.52
0.3
1.98
5.25
1.02
3.58
1,290
1
14.06
2.15
2.61
17.6
121
2.6
2.51
0.31
1.25
5.05
1.06
3.58
1,295
1
14.83
1.64
2.17
14
97
2.8
2.98
0.29
1.98
5.2
1.08
2.85
1,045
1
13.86
1.35
2.27
16
98
2.98
3.15
0.22
1.85
7.22
1.01
3.55
1,045
1
14.1
2.16
2.3
18
105
2.95
3.32
0.22
2.38
5.75
1.25
3.17
1,510
1
14.12
1.48
2.32
16.8
95
2.2
2.43
0.26
1.57
5
1.17
2.82
1,280
1
13.75
1.73
2.41
16
89
2.6
2.76
0.29
1.81
5.6
1.15
2.9
1,320
1
14.75
1.73
2.39
11.4
91
3.1
3.69
0.43
2.81
5.4
1.25
2.73
1,150
1
14.38
1.87
2.38
12
102
3.3
3.64
0.29
2.96
7.5
1.2
3
1,547
1
13.63
1.81
2.7
17.2
112
2.85
2.91
0.3
1.46
7.3
1.28
2.88
1,310
1
14.3
1.92
2.72
20
120
2.8
3.14
0.33
1.97
6.2
1.07
2.65
1,280
1
13.83
1.57
2.62
20
115
2.95
3.4
0.4
1.72
6.6
1.13
2.57
1,130
1
14.19
1.59
2.48
16.5
108
3.3
3.93
0.32
1.86
8.7
1.23
2.82
1,680
1
13.64
3.1
2.56
15.2
116
2.7
3.03
0.17
1.66
5.1
0.96
3.36
845
1
14.06
1.63
2.28
16
126
3
3.17
0.24
2.1
5.65
1.09
3.71
780
1
12.93
3.8
2.65
18.6
102
2.41
2.41
0.25
1.98
4.5
1.03
3.52
770
1
13.71
1.86
2.36
16.6
101
2.61
2.88
0.27
1.69
3.8
1.11
4
1,035
1
12.85
1.6
2.52
17.8
95
2.48
2.37
0.26
1.46
3.93
1.09
3.63
1,015
1
13.5
1.81
2.61
20
96
2.53
2.61
0.28
1.66
3.52
1.12
3.82
845
1
13.05
2.05
3.22
25
124
2.63
2.68
0.47
1.92
3.58
1.13
3.2
830
1
13.39
1.77
2.62
16.1
93
2.85
2.94
0.34
1.45
4.8
0.92
3.22
1,195
1
13.3
1.72
2.14
17
94
2.4
2.19
0.27
1.35
3.95
1.02
2.77
1,285
1
13.87
1.9
2.8
19.4
107
2.95
2.97
0.37
1.76
4.5
1.25
3.4
915
1
14.02
1.68
2.21
16
96
2.65
2.33
0.26
1.98
4.7
1.04
3.59
1,035
1
13.73
1.5
2.7
22.5
101
3
3.25
0.29
2.38
5.7
1.19
2.71
1,285
1
13.58
1.66
2.36
19.1
106
2.86
3.19
0.22
1.95
6.9
1.09
2.88
1,515
1
13.68
1.83
2.36
17.2
104
2.42
2.69
0.42
1.97
3.84
1.23
2.87
990
1
13.76
1.53
2.7
19.5
132
2.95
2.74
0.5
1.35
5.4
1.25
3
1,235
1
13.51
1.8
2.65
19
110
2.35
2.53
0.29
1.54
4.2
1.1
2.87
1,095
1
13.48
1.81
2.41
20.5
100
2.7
2.98
0.26
1.86
5.1
1.04
3.47
920
1
13.28
1.64
2.84
15.5
110
2.6
2.68
0.34
1.36
4.6
1.09
2.78
880
1
13.05
1.65
2.55
18
98
2.45
2.43
0.29
1.44
4.25
1.12
2.51
1,105
1
13.07
1.5
2.1
15.5
98
2.4
2.64
0.28
1.37
3.7
1.18
2.69
1,020
1
14.22
3.99
2.51
13.2
128
3
3.04
0.2
2.08
5.1
0.89
3.53
760
1
13.56
1.71
2.31
16.2
117
3.15
3.29
0.34
2.34
6.13
0.95
3.38
795
1
13.41
3.84
2.12
18.8
90
2.45
2.68
0.27
1.48
4.28
0.91
3
1,035
1
13.88
1.89
2.59
15
101
3.25
3.56
0.17
1.7
5.43
0.88
3.56
1,095
1
13.24
3.98
2.29
17.5
103
2.64
2.63
0.32
1.66
4.36
0.82
3
680
1
13.05
1.77
2.1
17
107
3
3
0.28
2.03
5.04
0.88
3.35
885
1
14.21
4.04
2.44
18.9
111
2.85
2.65
0.3
1.25
5.24
0.87
3.33
1,080
1
14.38
3.59
2.28
16
102
3.25
3.17
0.27
2.19
4.9
1.04
3.44
1,065
1
13.9
1.68
2.12
16
101
3.1
3.39
0.21
2.14
6.1
0.91
3.33
985
1
14.1
2.02
2.4
18.8
103
2.75
2.92
0.32
2.38
6.2
1.07
2.75
1,060
1
13.94
1.73
2.27
17.4
108
2.88
3.54
0.32
2.08
8.9
1.12
3.1
1,260
1
13.05
1.73
2.04
12.4
92
2.72
3.27
0.17
2.91
7.2
1.12
2.91
1,150
1
13.83
1.65
2.6
17.2
94
2.45
2.99
0.22
2.29
5.6
1.24
3.37
1,265
1
13.82
1.75
2.42
14
111
3.88
3.74
0.32
1.87
7.05
1.01
3.26
1,190
1
13.77
1.9
2.68
17.1
115
3
2.79
0.39
1.68
6.3
1.13
2.93
1,375
1
13.74
1.67
2.25
16.4
118
2.6
2.9
0.21
1.62
5.85
0.92
3.2
1,060
1
13.56
1.73
2.46
20.5
116
2.96
2.78
0.2
2.45
6.25
0.98
3.03
1,120
1
14.22
1.7
2.3
16.3
118
3.2
3
0.26
2.03
6.38
0.94
3.31
970
1
13.29
1.97
2.68
16.8
102
3
3.23
0.31
1.66
6
1.07
2.84
1,270
1
13.72
1.43
2.5
16.7
108
3.4
3.67
0.19
2.04
6.8
0.89
2.87
1,285
2
12.37
0.94
1.36
10.6
88
1.98
0.57
0.28
0.42
1.95
1.05
1.82
520
2
12.33
1.1
2.28
16
101
2.05
1.09
0.63
0.41
3.27
1.25
1.67
680
2
12.64
1.36
2.02
16.8
100
2.02
1.41
0.53
0.62
5.75
0.98
1.59
450
2
13.67
1.25
1.92
18
94
2.1
1.79
0.32
0.73
3.8
1.23
2.46
630
2
12.37
1.13
2.16
19
87
3.5
3.1
0.19
1.87
4.45
1.22
2.87
420
2
12.17
1.45
2.53
19
104
1.89
1.75
0.45
1.03
2.95
1.45
2.23
355
2
12.37
1.21
2.56
18.1
98
2.42
2.65
0.37
2.08
4.6
1.19
2.3
678
2
13.11
1.01
1.7
15
78
2.98
3.18
0.26
2.28
5.3
1.12
3.18
502
2
12.37
1.17
1.92
19.6
78
2.11
2
0.27
1.04
4.68
1.12
3.48
510
2
13.34
0.94
2.36
17
110
2.53
1.3
0.55
0.42
3.17
1.02
1.93
750
2
12.21
1.19
1.75
16.8
151
1.85
1.28
0.14
2.5
2.85
1.28
3.07
718
2
12.29
1.61
2.21
20.4
103
1.1
1.02
0.37
1.46
3.05
0.906
1.82
870
2
13.86
1.51
2.67
25
86
2.95
2.86
0.21
1.87
3.38
1.36
3.16
410
2
13.49
1.66
2.24
24
87
1.88
1.84
0.27
1.03
3.74
0.98
2.78
472
2
12.99
1.67
2.6
30
139
3.3
2.89
0.21
1.96
3.35
1.31
3.5
985
2
11.96
1.09
2.3
21
101
3.38
2.14
0.13
1.65
3.21
0.99
3.13
886
2
11.66
1.88
1.92
16
97
1.61
1.57
0.34
1.15
3.8
1.23
2.14
428
2
13.03
0.9
1.71
16
86
1.95
2.03
0.24
1.46
4.6
1.19
2.48
392
2
11.84
2.89
2.23
18
112
1.72
1.32
0.43
0.95
2.65
0.96
2.52
500
2
12.33
0.99
1.95
14.8
136
1.9
1.85
0.35
2.76
3.4
1.06
2.31
750
2
12.7
3.87
2.4
23
101
2.83
2.55
0.43
1.95
2.57
1.19
3.13
463
2
12
0.92
2
19
86
2.42
2.26
0.3
1.43
2.5
1.38
3.12
278
2
12.72
1.81
2.2
18.8
86
2.2
2.53
0.26
1.77
3.9
1.16
3.14
714
2
12.08
1.13
2.51
24
78
2
1.58
0.4
1.4
2.2
1.31
2.72
630
2
13.05
3.86
2.32
22.5
85
1.65
1.59
0.61
1.62
4.8
0.84
2.01
515
2
11.84
0.89
2.58
18
94
2.2
2.21
0.22
2.35
3.05
0.79
3.08
520
2
12.67
0.98
2.24
18
99
2.2
1.94
0.3
1.46
2.62
1.23
3.16
450
2
12.16
1.61
2.31
22.8
90
1.78
1.69
0.43
1.56
2.45
1.33
2.26
495
2
11.65
1.67
2.62
26
88
1.92
1.61
0.4
1.34
2.6
1.36
3.21
562
2
11.64
2.06
2.46
21.6
84
1.95
1.69
0.48
1.35
2.8
1
2.75
680
2
12.08
1.33
2.3
23.6
70
2.2
1.59
0.42
1.38
1.74
1.07
3.21
625
2
12.08
1.83
2.32
18.5
81
1.6
1.5
0.52
1.64
2.4
1.08
2.27
480
2
12
1.51
2.42
22
86
1.45
1.25
0.5
1.63
3.6
1.05
2.65
450
2
12.69
1.53
2.26
20.7
80
1.38
1.46
0.58
1.62
3.05
0.96
2.06
495
2
12.29
2.83
2.22
18
88
2.45
2.25
0.25
1.99
2.15
1.15
3.3
290
2
11.62
1.99
2.28
18
98
3.02
2.26
0.17
1.35
3.25
1.16
2.96
345
2
12.47
1.52
2.2
19
162
2.5
2.27
0.32
3.28
2.6
1.16
2.63
937
2
11.81
2.12
2.74
21.5
134
1.6
0.99
0.14
1.56
2.5
0.95
2.26
625
2
12.29
1.41
1.98
16
85
2.55
2.5
0.29
1.77
2.9
1.23
2.74
428
2
12.37
1.07
2.1
18.5
88
3.52
3.75
0.24
1.95
4.5
1.04
2.77
660
2
12.29
3.17
2.21
18
88
2.85
2.99
0.45
2.81
2.3
1.42
2.83
406
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Dataset Card for Wine Recognition dataset

Dataset Summary

These data are the results of a chemical analysis of wines grown in the same region in Italy but derived from three different cultivars. The analysis determined the quantities of 13 constituents found in each of the three types of wines. In a classification context, this is a well posed problem with "well behaved" class structures. A good data set for first testing of a new classifier, but not very challenging.

Supported Tasks and Leaderboards

Classification (cultivar) from continuous variables (all other variables)

Dataset Structure

Data Instances

178 wines

Data Fields

  1. Wine category (cultivar)
  2. Alcohol
  3. Malic acid
  4. Ash
  5. Alcalinity of ash
  6. Magnesium
  7. Total phenols
  8. Flavanoids
  9. Nonflavanoid phenols
  10. Proanthocyanins
  11. Color intensity
  12. Hue
  13. OD280/OD315 of diluted wines
  14. Proline

Data Splits

None

Dataset Creation

Source Data

https://archive.ics.uci.edu/ml/datasets/wine

Initial Data Collection and Normalization

Original Owners:

Forina, M. et al, PARVUS - An Extendible Package for Data Exploration, Classification and Correlation. Institute of Pharmaceutical and Food Analysis and Technologies, Via Brigata Salerno, 16147 Genoa, Italy.

Additional Information

Dataset Curators

Stefan Aeberhard

Licensing Information

No information found on the original website

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Edit dataset card
Homepage:
archive.ics.uci.edu
Papers:
Papers:
Point of Contact:
stefan'@'coral.cs.jcu.edu.au
Size of downloaded dataset files:
11 kB
Size of the auto-converted Parquet files:
15.9 kB
Number of rows:
178