Iris
Donated on 6/30/1988
A small classic dataset from Fisher, 1936. One of the earliest known datasets used for evaluating classification methods.
Dataset Characteristics
Tabular
Subject Area
Biology
Associated Tasks
Classification
Feature Type
Real
# Instances
150
# Features
4
Dataset Information
What do the instances in this dataset represent?
Each instance is a plant
Additional Information
This is one of the earliest datasets used in the literature on classification methods and widely used in statistics and machine learning. 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, [email protected] ). 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.
Has Missing Values?
No
Introductory Paper
By A. Unwin, K. Kleinman. 2021
Published in Significance, 2021
Variables Table
Variable Name | Role | Type | Description | Units | Missing Values |
---|---|---|---|---|---|
sepal length | Feature | Continuous | cm | no | |
sepal width | Feature | Continuous | cm | no | |
petal length | Feature | Continuous | cm | no | |
petal width | Feature | Continuous | cm | no | |
class | Target | Categorical | class of iris plant: Iris Setosa, Iris Versicolour, or Iris Virginica | no |
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Baseline Model Performance
Dataset Files
File | Size |
---|---|
bezdekIris.data | 4.4 KB |
iris.data | 4.4 KB |
iris.names | 2.9 KB |
Index | 105 Bytes |
Papers Citing this Dataset
Sort by Year, desc
By W. Daniel, Enoch Yeung. 2019
Published in ArXiv.
By Zachary Charles, Shashank Rajput, Stephen Wright, Dimitris Papailiopoulos. 2019
Published in ArXiv.
By Xin Huang, Yulia Gel. 2019
Published in 2017 IEEE International Conference on Data Mining (ICDM), 925--930} (2017).
By Jibin Wu, Yansong Chua, Malu Zhang, Qu Yang, Guoqi Li, Haizhou Li. 2019
Published in ArXiv.
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset iris = fetch_ucirepo(id=53) # data (as pandas dataframes) X = iris.data.features y = iris.data.targets # metadata print(iris.metadata) # variable information print(iris.variables)
Fisher, R. (1936). Iris [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C56C76.
Keywords
Creators
R. A. Fisher
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.