Answered: K-Nearest Neighbor method for…

Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

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Question

the hello-world machine learning project employees a K-Nearest Neighbor method for classification problems How does parameter K affect the prediction accuracy?

Expert Solution

Step 1

KNN algorithm fairs across all parameters of considerations. It is commonly used for its easy of interpretation and low calculation time.

In data science context, it is not necessarily true that more number of input parameters will predict output/target feature accurately. In fact, if the input parameters are not strongly correlated to the output feature, they may result in lower prediction accuracy. Please go through the attached paper, where I have talked about this problem and I show that by carefully performing feature selection lower number of parameters give higher prediction accuracy.