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.
Make you follow all of them so you don’t lose any grade points because of that. Feel free to contact me for any questions you may have.
Delivering a high-quality product at a reasonable price is not enough anymore.
That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.
You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.Read more
Each paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.Read more
Thanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.Read more
Your email is safe, as we store it according to international data protection rules. Your bank details are secure, as we use only reliable payment systems.Read more
By sending us your money, you buy the service we provide. Check out our terms and conditions if you prefer business talks to be laid out in official language.Read more