Iris Flowers

Dataset

Title: Iris Plants Database

Updated Sept 21 by C. Blake - Added discrepancy information

Sources:

• Creator: R.A. Fisher
• Donor: Michael Marshall (MARSHALL%[email protected])
• Date: July, 1988

Past Usage:

Publications: too many to mention!!! Here are a few:

1. Fisher,R.A. "The use of multiple measurements in taxonomic problems" Annual Eugenics, 7, Part II, 179-188 (1936); also in "Contributions to Mathematical Statistics" (John Wiley, NY, 1950). Duda,R.O., & Hart,P.E. (1973) Pattern Classification and Scene Analysis. (Q327.D83) John Wiley & Sons. ISBN 0-471-22361-1. See page 218.
2. Dasarathy, B.V. (1980) "Nosing Around the Neighborhood: A New System Structure and Classification Rule for Recognition in Partially Exposed Environments". IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-2, No. 1, 67-71. -- Results: -- very low misclassification rates (0% for the setosa class)
3. Gates, G.W. (1972) "The Reduced Nearest Neighbor Rule". IEEE Transactions on Information Theory, May 1972, 431-433. -- Results: -- very low misclassification rates again
4. See also: 1988 MLC Proceedings, 54-64. Cheeseman et al's AUTOCLASS II conceptual clustering system finds 3 classes in the data.

Relevant Information:

• 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, [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.

Number of Instances: 150 (50 in each of three classes)

Number of Attributes: 4 numeric, predictive attributes and the class

Attribute Information:

1. Sepal length in cm
2. Sepal width in cm
3. Petal length in cm
4. Petal width in cm
5. Class:
   • Iris Setosa
   • Iris Versicolour
   • Iris Virginica

Missing Attribute Values: None

Summary Statistics:

	Min	Max	Mean	SD	Class Correlation
Sepal length	4.3	7.9	5.84	0.83	0.7826
Sepal width	2.0	4.4	3.05	0.43	-0.4194
Petal length	1.0	6.9	3.76	1.76	0.9490 (high!)
Petal width	0.1	2.5	1.20	0.76	0.9565 (high!)

Class Distribution: 33.3% for each of 3 classes.