Simple Classification program to predict the species of an iris flower.
This project is used to classify the different species of iris floweMachine Learning Project : Iris-flower-classification
This program applies basic machine learning (classification) concepts on Iris Data to predict the species of a new sample of Iris flower.
Python 3.6.0
Anaconda 4.3.0 (32 bit)
scikit-learn 0.18.1
The dataset for this project originates from the UCI Machine Learning Repository. 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.
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 (in centimetres):
Length of the sepals
Width of the sepals
Length of the petals
Width of the petals.
For detiled view of project description :
@swarupachowdaryp/iris-flower-classification-using-machine-learning-48e0bde76e41"">https://medium.com/@swarupachowdaryp/iris-flower-classification-using-machine-learning-48e0bde76e41