Iris Classification using Decision Tree

Xiang Jiang
Aug 24 2014

Introduction to Dataset

The Iris dataset has five variables:

[1] "Sepal.Length" "Sepal.Width"  "Petal.Length" "Petal.Width" 
[5] "Species"

The first four variables are used for classification, and the last variable Species is the target variable.

Exploratory Data Analysis

In the Shiny application, we can visualize the dataset by specifying x and y axis yourself.

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From exploratory analysis, we find that different species of Iris are separable from the features we have.

Building the Decision Tree

We now build the decision tree and visualize the tree as follows.

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Making Predictions

In the Shiny app, user can select values for the four features of the input, and a prediction for the specie will be made and shown in the Predictions panel.