What do you think the optimal value of k might be

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Question 1: Explain supervised learning in your own words. Put yourself in the shoes of someone without any clue what it is--and help them understand it. Minimum 75 words.

Question 2: Explain the k-nearest-neighbor algorithm, and discuss its pros and cons as a supervised learning algorithm. Does it scale well to datasets with a large number of features? Minimum 75 words.
The original article links for this assignment are posted in Canvas, but I have edited them and produced PDFs for easier access:

Question 3. What do you think the optimal value of k might be for the iris dataset (in this case only using the sepal width and length as the two features)?

Reference no: EM133769298

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