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iris-flower-classification-project's Introduction

Machine Learning Project:Iris-Flower-Classification-Project

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.

Software and Libraries

Python 3.6.0 Anaconda 4.3.0 (32 bit) scikit-learn 0.18.1

Introduction

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 : https://medium.com/@swarupachowdaryp/iris-flower-classification-using-machine-learning-48e0bde76e41

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