In the early 1930's, Edgar Anderson collected data on three iris species in the Gaspe penisula: virginica, setosa, and versicolor. In 1936, R. A. Fisher used this data in his paper on discriminate analysis in which he described a method for distinguishing between the species. Since then, this data set has become ubiquitious for testing Machine Learning algorithms.
This is a small data set with fifty observations for each species and with four predictors: pedal length, petal width, sepal length, and sepal width. Yet it is challenging to be able to provide an error free classification.
For this project we have provided users with an application that when given values of the parameters will then predict which of the three species is described by those parameters.