Apply Machine Learning Classification Models to Iris Flowers Dataset 

/in /by

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:

  1. 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.
  2. Preprocess the iris.csv file by label encoding the target ‘variety’ column.
  3. Apply the following Machine Learning classification models: K Nearest Neighbors and Random Forests
  4. Calculate the following classification metrics to validate the model: Accuracy Score, Confusion Matrix and Classification Report
  5. Explain how the program works and compare these two classification models

Requirements:

  • 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.