Datasets:

Modalities:
Tabular
Text
Formats:
csv
Size:
< 1K
Libraries:
Datasets
pandas
License:
Id
int64
1
150
SepalLengthCm
float64
4.3
7.9
SepalWidthCm
float64
2
4.4
PetalLengthCm
float64
1
6.9
PetalWidthCm
float64
0.1
2.5
Species
stringclasses
3 values
1
5.1
3.5
1.4
0.2
Iris-setosa
2
4.9
3
1.4
0.2
Iris-setosa
3
4.7
3.2
1.3
0.2
Iris-setosa
4
4.6
3.1
1.5
0.2
Iris-setosa
5
5
3.6
1.4
0.2
Iris-setosa
6
5.4
3.9
1.7
0.4
Iris-setosa
7
4.6
3.4
1.4
0.3
Iris-setosa
8
5
3.4
1.5
0.2
Iris-setosa
9
4.4
2.9
1.4
0.2
Iris-setosa
10
4.9
3.1
1.5
0.1
Iris-setosa
11
5.4
3.7
1.5
0.2
Iris-setosa
12
4.8
3.4
1.6
0.2
Iris-setosa
13
4.8
3
1.4
0.1
Iris-setosa
14
4.3
3
1.1
0.1
Iris-setosa
15
5.8
4
1.2
0.2
Iris-setosa
16
5.7
4.4
1.5
0.4
Iris-setosa
17
5.4
3.9
1.3
0.4
Iris-setosa
18
5.1
3.5
1.4
0.3
Iris-setosa
19
5.7
3.8
1.7
0.3
Iris-setosa
20
5.1
3.8
1.5
0.3
Iris-setosa
21
5.4
3.4
1.7
0.2
Iris-setosa
22
5.1
3.7
1.5
0.4
Iris-setosa
23
4.6
3.6
1
0.2
Iris-setosa
24
5.1
3.3
1.7
0.5
Iris-setosa
25
4.8
3.4
1.9
0.2
Iris-setosa
26
5
3
1.6
0.2
Iris-setosa
27
5
3.4
1.6
0.4
Iris-setosa
28
5.2
3.5
1.5
0.2
Iris-setosa
29
5.2
3.4
1.4
0.2
Iris-setosa
30
4.7
3.2
1.6
0.2
Iris-setosa
31
4.8
3.1
1.6
0.2
Iris-setosa
32
5.4
3.4
1.5
0.4
Iris-setosa
33
5.2
4.1
1.5
0.1
Iris-setosa
34
5.5
4.2
1.4
0.2
Iris-setosa
35
4.9
3.1
1.5
0.1
Iris-setosa
36
5
3.2
1.2
0.2
Iris-setosa
37
5.5
3.5
1.3
0.2
Iris-setosa
38
4.9
3.1
1.5
0.1
Iris-setosa
39
4.4
3
1.3
0.2
Iris-setosa
40
5.1
3.4
1.5
0.2
Iris-setosa
41
5
3.5
1.3
0.3
Iris-setosa
42
4.5
2.3
1.3
0.3
Iris-setosa
43
4.4
3.2
1.3
0.2
Iris-setosa
44
5
3.5
1.6
0.6
Iris-setosa
45
5.1
3.8
1.9
0.4
Iris-setosa
46
4.8
3
1.4
0.3
Iris-setosa
47
5.1
3.8
1.6
0.2
Iris-setosa
48
4.6
3.2
1.4
0.2
Iris-setosa
49
5.3
3.7
1.5
0.2
Iris-setosa
50
5
3.3
1.4
0.2
Iris-setosa
51
7
3.2
4.7
1.4
Iris-versicolor
52
6.4
3.2
4.5
1.5
Iris-versicolor
53
6.9
3.1
4.9
1.5
Iris-versicolor
54
5.5
2.3
4
1.3
Iris-versicolor
55
6.5
2.8
4.6
1.5
Iris-versicolor
56
5.7
2.8
4.5
1.3
Iris-versicolor
57
6.3
3.3
4.7
1.6
Iris-versicolor
58
4.9
2.4
3.3
1
Iris-versicolor
59
6.6
2.9
4.6
1.3
Iris-versicolor
60
5.2
2.7
3.9
1.4
Iris-versicolor
61
5
2
3.5
1
Iris-versicolor
62
5.9
3
4.2
1.5
Iris-versicolor
63
6
2.2
4
1
Iris-versicolor
64
6.1
2.9
4.7
1.4
Iris-versicolor
65
5.6
2.9
3.6
1.3
Iris-versicolor
66
6.7
3.1
4.4
1.4
Iris-versicolor
67
5.6
3
4.5
1.5
Iris-versicolor
68
5.8
2.7
4.1
1
Iris-versicolor
69
6.2
2.2
4.5
1.5
Iris-versicolor
70
5.6
2.5
3.9
1.1
Iris-versicolor
71
5.9
3.2
4.8
1.8
Iris-versicolor
72
6.1
2.8
4
1.3
Iris-versicolor
73
6.3
2.5
4.9
1.5
Iris-versicolor
74
6.1
2.8
4.7
1.2
Iris-versicolor
75
6.4
2.9
4.3
1.3
Iris-versicolor
76
6.6
3
4.4
1.4
Iris-versicolor
77
6.8
2.8
4.8
1.4
Iris-versicolor
78
6.7
3
5
1.7
Iris-versicolor
79
6
2.9
4.5
1.5
Iris-versicolor
80
5.7
2.6
3.5
1
Iris-versicolor
81
5.5
2.4
3.8
1.1
Iris-versicolor
82
5.5
2.4
3.7
1
Iris-versicolor
83
5.8
2.7
3.9
1.2
Iris-versicolor
84
6
2.7
5.1
1.6
Iris-versicolor
85
5.4
3
4.5
1.5
Iris-versicolor
86
6
3.4
4.5
1.6
Iris-versicolor
87
6.7
3.1
4.7
1.5
Iris-versicolor
88
6.3
2.3
4.4
1.3
Iris-versicolor
89
5.6
3
4.1
1.3
Iris-versicolor
90
5.5
2.5
4
1.3
Iris-versicolor
91
5.5
2.6
4.4
1.2
Iris-versicolor
92
6.1
3
4.6
1.4
Iris-versicolor
93
5.8
2.6
4
1.2
Iris-versicolor
94
5
2.3
3.3
1
Iris-versicolor
95
5.6
2.7
4.2
1.3
Iris-versicolor
96
5.7
3
4.2
1.2
Iris-versicolor
97
5.7
2.9
4.2
1.3
Iris-versicolor
98
6.2
2.9
4.3
1.3
Iris-versicolor
99
5.1
2.5
3
1.1
Iris-versicolor
100
5.7
2.8
4.1
1.3
Iris-versicolor

Iris Species Dataset

The Iris dataset was used in R.A. Fisher's classic 1936 paper, The Use of Multiple Measurements in Taxonomic Problems, and can also be found on the UCI Machine Learning Repository.

It includes three iris species with 50 samples each as well as some properties about each flower. One flower species is linearly separable from the other two, but the other two are not linearly separable from each other. The dataset is taken from UCI Machine Learning Repository's Kaggle. The following description is taken from UCI Machine Learning Repository. This is perhaps the best known database to be found in the pattern recognition literature. Fisher's paper is a classic in the field and is referenced frequently to this day. (See Duda & Hart, for example.) The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant. One class is linearly separable from the other 2; the latter are NOT linearly separable from each other.

Predicted attribute: class of iris plant.

This is an exceedingly simple domain.

This data differs from the data presented in Fishers article (identified by Steve Chadwick, spchadwick '@' espeedaz.net ). The 35th sample should be: 4.9,3.1,1.5,0.2,"Iris-setosa" where the error is in the fourth feature. The 38th sample: 4.9,3.6,1.4,0.1,"Iris-setosa" where the errors are in the second and third features.

Features in this dataset are the following:

  • sepal length in cm
  • sepal width in cm
  • petal length in cm
  • petal width in cm
  • class:
    • Iris Setosa
    • Iris Versicolour
    • Iris Virginica
Downloads last month
5,799
Edit dataset card

Models trained or fine-tuned on scikit-learn/iris

Space using scikit-learn/iris 1