# Info on Iris Plants Data Base

    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.