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.
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 centimetres. Based on the combination of these four features, Fisher developed a linear discriminant model to distinguish the species from each other.
The k-Nearest Neighbors calculation (or kNN for short) is a simple calculation to comprehend and to actualize, and an intense instrument to have available to you.
Used Python 2.7 for KNN.py
Used Python 3.6.1 for KNN-sklearn.ipynb
The implementation will be specific to classification problems and will be demonstrated using the Iris flowers classification problem.
Get the dataset: iris.data