Slide 1: Prediction of Iris Species

This is a presentation on Prediction of Iris Species using Shiny

This project aims to develop a predictive model for classifying iris flower species based on their petal and sepal dimensions. Using the well-known Iris dataset, which contains measurements for three species—Setosa, Versicolor, and Virginica—the application leverages a nearest neighbors algorithm to determine the likely species based on user-provided measurements. By integrating the model into a Shiny web application, users can easily input dimensions and receive immediate species predictions.

Slide 2: Problem Statement & Objective

The presentation is about using nearest neighbors to predict the species of a flower as Setosa, Versicolor or virginica from the iris dataset available in R. Main Features:

• Predicts species of flowers from the iris dataset
• Uses Shiny Application
• Uses RStudio Presenter

Setosa

Versicolor

Virginica

Slide 3: Prediction Methodology

Working of the application

• step 1: collect user input
• step 2: calculate euclidian distance of all points from input
• step 3: find the nearest neighbour
• step 4: render the output

Slide 4: Demonstration of the Shiny App

you can run the application using the link below :

• Open the link
• enter the petal length and petal width (max value = 7cm)
• click ‘predict’

Run My Shiny App

Sample output image:

Slide 5: Resources

Link to the Coursera course

Link to github repository of my shiny application