Develop a k-nearest neighbor (kNN)
Q2. The attached Excel file Iris.xlsx lists a dataset that consists of samples from each of three flower species of Iris (Iris setosa, Iris virginica and Iris versicolor) and 4 attributes – Petal Length, Petal Width, Sepal Length, Sepal width. The dataset has been partitioned to training and testing set. Develop a k-nearest neighbor (kNN) model that predicts the class of the test sets given the attribute information. Assume that the model uses Euclidean distance to find the nearest neighbor using k=1. Show all the calculation steps in Excel for the prediction the testing set classes. Develop a confusion matrix of the predicted and actual class. Calculate overall classifier accuracy from the confusion matrix. Do not use Weka or rattle for this exercise, use only Excel. Upload the Excel file showing all the calculation details.
We've got everything to become your favourite writing service
Money back guarantee
Your money is safe. Even if we fail to satisfy your expectations, you can always request a refund and get your money back.
Confidentiality
We don’t share your private information with anyone. What happens on our website stays on our website.
Our service is legit
We provide you with a sample paper on the topic you need, and this kind of academic assistance is perfectly legitimate.
Get a plagiarism-free paper
We check every paper with our plagiarism-detection software, so you get a unique paper written for your particular purposes.
We can help with urgent tasks
Need a paper tomorrow? We can write it even while you’re sleeping. Place an order now and get your paper in 8 hours.
Pay a fair price
Our prices depend on urgency. If you want a cheap essay, place your order in advance. Our prices start from $11 per page.