trisa-biswas / r-shiny-dashboard-for-iris-classification-problem

The purpose of this project is to allow a user to upload the Iris Dataset, check summary and then predict the classification of the Iris flower.

R-Shiny-Dashboard-for-IRIS-Classification-Problem

The purpose of this project is to allow a user to upload the Iris Dataset, check summary and then predict the classification of the Iris flower.
The dataset has been downloaded from UCI's Machine Learning Repository. Here: https://archive.ics.uci.edu/ml/datasets/iris

This data set consists of the physical parameters of three species of flower — Versicolor, Setosa and Virginica. The numeric parameters which the dataset contains are Sepal width, Sepal length, Petal width and Petal length. In this data we will be predicting the classes of the flowers based on these parameters.The data consists of continuous numeric values which describe the dimensions of the respective features. We will be training the model based on these features. We have built our model based on the KNN Algorithm.
The dashboard allows a user to upload a file and predict the results. Prediction can also be made on the fly by manually entering the inputs.