Apply Machine Learning Classification Models to Iris Flowers Dataset
Write a program to apply Machine Learning classification models to Iris flowers dataset. Follow the steps:
- Download the iris.csv file (example: https://gist.github.com/netj/8836201). From this file the label (target) is defined with the ‘variety’ column and the features with ‘epal.length’, ‘sepal.width’, ‘petal.length’, ‘petal.width’ columns.
- Preprocess the iris.csv file by label encoding the target ‘variety’ column.
- Apply the following Machine Learning classification models: K Nearest Neighbors and Random Forests
- Calculate the following classification metrics to validate the model: Accuracy Score, Confusion Matrix and Classification Report
- Explain how the program works and compare these two classification models
- Maximum four to five pages in length is required.
- You must include program code and results.
- You must include an explanation about how the program works.
- You must show your work for full credit.
- You must include a minimum of three credible sources. Use the Saudi Electronic Digital Library to find your resources.
- Your paper must follow Saudi Electronic University academic writing standards and APA style guidelines, as appropriate.