Iris Flower Classification Project Report
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.
Iris flower classification project report. Attributes are numeric so you have to figure out how to load and handle data. In this video we will be working on our first project on iris flower classification. This is a good project because it is so well understood. This project is basically used to differentiate between three species of the iris flower which are setosa versicolor and virginica.
The dataset for this project originates from the uci machine learning repository. The aim is to classify iris flowers among three species setosa versicolor or virginica from measurements of sepals and petals length and width. The iris data set contains 3 classes of 50 instances each where each class refers to a type of iris plant. It focuses on iris flower classification using machine learning with scikit tools.
The best small project to start with on a new tool is the classification of iris flowers e g. Iris flower classification this project is thorugh application of machine learning with python programming. The iris flower data set or fisher s iris data set is a multivariate data set introduced by the british statistician eugenicist and biologist ronald fisher in his 1936 paper the use of multiple measurements in taxonomic problems as an example of linear discriminant analysis. In this project the object is the iris flower.
Looking to build projects on machine learning. Here some of algorithm are used that are some types of machine learning subparts algorithms of supervised and unsupervised learning. It is sometimes called anderson s iris data set because edgar anderson collected the data to quantify the morphologic. Welcome to the part two of the machine learning tutorial today we are going to develop the model that is going to classify the iris flowers for us before we get started to the problem i recommend.
It is a classification problem allowing you to practice with perhaps an easier type of supervised learning algorithm. 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. The data set of iris contains three different classes.
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