Fisher's Iris Data Base of 1936

Fisher's Iris Data Base of 1936 is a small low-dimensional i.i.d. data base that represents Iris presented in (Anderson, 1935) and made famous by (Fisher, 1936).

• Context:
  • It can be used in a Iris Dataset-based Classification Task, Iris Dataset-based Clustering Task, ...
  • It can be attributed to (Anderson, 1935).
• Example(s):
  • the one at http://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data
• Counter-Example(s):
  • digits Dataset.
  • Piazzi's Ceres Dataset of 1801.
• See: UCI Dataset, Benchmark Data, Fisher's Discriminant Analysis, Iris (Plant).

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References

2020

• (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/Iris_flower_data_set Retrieved:2020-3-6.
  • The Iris flower data set or Fisher's Iris data set is a multivariate data set introduced by the British statistician and biologist Ronald Fisher in his 1936 paper The use of multiple measurements in taxonomic problems as an example of linear discriminant analysis. It is sometimes called Anderson's Iris data set because Edgar Anderson collected the data to quantify the morphologic variation of Iris flowers of three related species. Two of the three species were collected in the Gaspé Peninsula "all from the same pasture, and picked on the same day and measured at the same time by the same person with the same apparatus".

    The data set consists of 50 samples from each of three species of Iris (Iris setosa, Iris virginica and Iris versicolor). Four features were measured from each sample: the length and the width of the sepals and petals, in centimeters. Based on the combination of these four features, Fisher developed a linear discriminant model to distinguish the species from each other.

2011

• http://archive.ics.uci.edu/ml/datasets/Iris/
  • 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. …

     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

1980

• B. V. Dasarathy. (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.

1973

• (Duda & Hart, 1973) ⇒ R. O. Duda, and P. E. Hart. (1973) Pattern Classification and Scene Analysis. (Q327.D83) John Wiley & Sons. ISBN 0-471-22361-1. See page 218.

1972

• (Gates, 1972) ⇒ G. W. Gates. (1972) "The Reduced Nearest Neighbor Rule". IEEE Transactions on Information Theory, May 1972, 431-433.

1936

• (Fisher, 1936) ⇒ Ronald A. Fisher. “The Use of Multiple Measurements in Taxonomic Problems.” In: Annual Eugenics, 7, Part II.

1935

• (Anderson, 1935) ⇒ Edgar Anderson. (1935). “The irises of the Gaspé Peninsula.” Bulletin of the American Iris Society, 59.

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