1. Nearest Neighbor Methods (9 Points): This question is on Nearest Neighbor Methods (a) (2 points) Nearest Neighbor Reg

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1. Nearest Neighbor Methods (9 Points): This question is on
Nearest Neighbor Methods
(a) (2 points) Nearest Neighbor Regression: In class, we looked
at k-Nearest Neighbor Classification. Can you extend this to
regression? What will the algorithm look like if we do Nearest
Neighbor Regression? Does it make sense to do regression with
nearest neighbors?
(b) (2 points) Irrelevant Attributes: Please give an example of
a dataset where a nearest neighbor algorithm would perform very
poorly when we have irrelevant features.
(c) Implementation (5 points): Implement a k-Nearest Neighbor
Algorithm from scratch on the dataset considered in the demo.
Compare your results with what we obtained in the demo using
sklearn. The link to the demo we did in class is
https://drive.google.com/drive/u/0/fold ... juUpN4p9OD.