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The Iris flower data set or Fisher's Iris data set is a multivariate data set used and made famous 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. [1]
The Iris data set is a public domain data set and it is built-in by default in R framework. Here's how to create the picture: ... Fix typo in virginica. 20:56, 9 ...
Iris virginica is a perennial plant that grows up to 0.6–0.9 m (2–3 ft) tall. The plant's sword-shaped basal leaves are erect or sometimes arching and measure up to 91 cm (3 ft) long and 2.5 cm (1 in) across at the base.
In 1936, he introduced the Iris flower data set as an example of discriminant analysis. [66] In his 1937 paper The wave of advance of advantageous genes he proposed Fisher's equation in the context of population dynamics to describe the spatial spread of an advantageous allele, and explored its travelling wave solutions. [67]
An example of a decision stump that discriminates between two of three classes of Iris flower data set: Iris versicolor and Iris virginica. The petal width is in centimetres. This particular stump achieves 94% accuracy on the Iris dataset for these two classes. A decision stump is a machine learning model consisting of a one-level decision tree ...
Iris laevigata Fisch – Rabbitear Iris, Shallow-flowered Iris, kakitsubata (Japanese) Iris maackii Maxim. Iris pseudacorus L. – Yellow Iris, Yellow Flag; Iris versicolor L. – Larger Blue Flag, Harlequin Blueflag; Iris virginica L. – Virginia Iris; Series Longipetalae (Rocky Mountain or long-petaled iris) Iris longipetala Herb. – (Coast ...
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English: Iris flower data set, clustered using k means (left) and true species in the data set (right). Note that k-means is non-determinicstic, so results vary. Cluster means are visualized using larger, semi-transparent markers. The visualization was generated using ELKI.