% 1. Title: Iris Plants Database % % 2. Sources: % (a) Creator: R.A. Fisher % (b) Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov) % (c) Date: July, 1988 % % 3. 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). % 2. 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. % 3. 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) % 4. Gates, G.W. (1972) "The Reduced Nearest Neighbor Rule". IEEE % Transactions on Information Theory, May 1972, 431-433. % -- Results: % -- very low misclassification rates again % 5. See also: 1988 MLC Proceedings, 54-64. Cheeseman et al's AUTOCLASS II % conceptual clustering system finds 3 classes in the data. % % 4. 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. % % 5. Number of Instances: 150 (50 in each of three classes) % % 6. Number of Attributes: 4 numeric, predictive attributes and the class % % 7. 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 % % 8. 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!) % % 9. Class Distribution: 33.3% for each of 3 classes. function [p,t]=iris(n) p = [ 5.1 3.5 1.4 0.2; 4.9 3.0 1.4 0.2; 4.7 3.2 1.3 0.2; 4.6 3.1 1.5 0.2; 5.0 3.6 1.4 0.2; 5.4 3.9 1.7 0.4; 4.6 3.4 1.4 0.3; 5.0 3.4 1.5 0.2; 4.4 2.9 1.4 0.2; 4.9 3.1 1.5 0.1; 5.4 3.7 1.5 0.2; 4.8 3.4 1.6 0.2; 4.8 3.0 1.4 0.1; 4.3 3.0 1.1 0.1; 5.8 4.0 1.2 0.2; 5.7 4.4 1.5 0.4; 5.4 3.9 1.3 0.4; 5.1 3.5 1.4 0.3; 5.7 3.8 1.7 0.3; 5.1 3.8 1.5 0.3; 5.4 3.4 1.7 0.2; 5.1 3.7 1.5 0.4; 4.6 3.6 1.0 0.2; 5.1 3.3 1.7 0.5; 4.8 3.4 1.9 0.2; 5.0 3.0 1.6 0.2; 5.0 3.4 1.6 0.4; 5.2 3.5 1.5 0.2; 5.2 3.4 1.4 0.2; 4.7 3.2 1.6 0.2; 4.8 3.1 1.6 0.2; 5.4 3.4 1.5 0.4; 5.2 4.1 1.5 0.1; 5.5 4.2 1.4 0.2; 4.9 3.1 1.5 0.1; 5.0 3.2 1.2 0.2; 5.5 3.5 1.3 0.2; 4.9 3.1 1.5 0.1; 4.4 3.0 1.3 0.2; 5.1 3.4 1.5 0.2; 5.0 3.5 1.3 0.3; 4.5 2.3 1.3 0.3; 4.4 3.2 1.3 0.2; 5.0 3.5 1.6 0.6; 5.1 3.8 1.9 0.4; 4.8 3.0 1.4 0.3; 5.1 3.8 1.6 0.2; 4.6 3.2 1.4 0.2; 5.3 3.7 1.5 0.2; 5.0 3.3 1.4 0.2; 7.0 3.2 4.7 1.4; 6.4 3.2 4.5 1.5; 6.9 3.1 4.9 1.5; 5.5 2.3 4.0 1.3; 6.5 2.8 4.6 1.5; 5.7 2.8 4.5 1.3; 6.3 3.3 4.7 1.6; 4.9 2.4 3.3 1.0; 6.6 2.9 4.6 1.3; 5.2 2.7 3.9 1.4; 5.0 2.0 3.5 1.0; 5.9 3.0 4.2 1.5; 6.0 2.2 4.0 1.0; 6.1 2.9 4.7 1.4; 5.6 2.9 3.6 1.3; 6.7 3.1 4.4 1.4; 5.6 3.0 4.5 1.5; 5.8 2.7 4.1 1.0; 6.2 2.2 4.5 1.5; 5.6 2.5 3.9 1.1; 5.9 3.2 4.8 1.8; 6.1 2.8 4.0 1.3; 6.3 2.5 4.9 1.5; 6.1 2.8 4.7 1.2; 6.4 2.9 4.3 1.3; 6.6 3.0 4.4 1.4; 6.8 2.8 4.8 1.4; 6.7 3.0 5.0 1.7; 6.0 2.9 4.5 1.5; 5.7 2.6 3.5 1.0; 5.5 2.4 3.8 1.1; 5.5 2.4 3.7 1.0; 5.8 2.7 3.9 1.2; 6.0 2.7 5.1 1.6; 5.4 3.0 4.5 1.5; 6.0 3.4 4.5 1.6; 6.7 3.1 4.7 1.5; 6.3 2.3 4.4 1.3; 5.6 3.0 4.1 1.3; 5.5 2.5 4.0 1.3; 5.5 2.6 4.4 1.2; 6.1 3.0 4.6 1.4; 5.8 2.6 4.0 1.2; 5.0 2.3 3.3 1.0; 5.6 2.7 4.2 1.3; 5.7 3.0 4.2 1.2; 5.7 2.9 4.2 1.3; 6.2 2.9 4.3 1.3; 5.1 2.5 3.0 1.1; 5.7 2.8 4.1 1.3; 6.3 3.3 6.0 2.5; 5.8 2.7 5.1 1.9; 7.1 3.0 5.9 2.1; 6.3 2.9 5.6 1.8; 6.5 3.0 5.8 2.2; 7.6 3.0 6.6 2.1; 4.9 2.5 4.5 1.7; 7.3 2.9 6.3 1.8; 6.7 2.5 5.8 1.8; 7.2 3.6 6.1 2.5; 6.5 3.2 5.1 2.0; 6.4 2.7 5.3 1.9; 6.8 3.0 5.5 2.1; 5.7 2.5 5.0 2.0; 5.8 2.8 5.1 2.4; 6.4 3.2 5.3 2.3; 6.5 3.0 5.5 1.8; 7.7 3.8 6.7 2.2; 7.7 2.6 6.9 2.3; 6.0 2.2 5.0 1.5; 6.9 3.2 5.7 2.3; 5.6 2.8 4.9 2.0; 7.7 2.8 6.7 2.0; 6.3 2.7 4.9 1.8; 6.7 3.3 5.7 2.1; 7.2 3.2 6.0 1.8; 6.2 2.8 4.8 1.8; 6.1 3.0 4.9 1.8; 6.4 2.8 5.6 2.1; 7.2 3.0 5.8 1.6; 7.4 2.8 6.1 1.9; 7.9 3.8 6.4 2.0; 6.4 2.8 5.6 2.2; 6.3 2.8 5.1 1.5; 6.1 2.6 5.6 1.4; 7.7 3.0 6.1 2.3; 6.3 3.4 5.6 2.4; 6.4 3.1 5.5 1.8; 6.0 3.0 4.8 1.8; 6.9 3.1 5.4 2.1; 6.7 3.1 5.6 2.4; 6.9 3.1 5.1 2.3; 5.8 2.7 5.1 1.9; 6.8 3.2 5.9 2.3; 6.7 3.3 5.7 2.5; 6.7 3.0 5.2 2.3; 6.3 2.5 5.0 1.9; 6.5 3.0 5.2 2.0; 6.2 3.4 5.4 2.3; 5.9 3.0 5.1 1.8; ]'; t = [ 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 1 0 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 1 0; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1; 0 0 1 ]';