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Aperture Science is a small company that sells information technology (IT) products. The lone data scientist at Aperture approaches you one day and proposes to use k-NN estimation to build an IT wallet estimation predictor to predict the wallet share that companies will spend with you. They would like your help building and deploying the model. The only data you have on hand is the total IT budgets of a large set of companies, which will make up your database of potential neighbors. Ultimately, you want to estimate your wallet share for Acme Corp., one of your current customers for whom you do not know the IT budget.
NOTE: Wallet share is the percentage of a company's total IT budget that is spent with your company. So, for example, if a company spent 25% of its IT budget with Aperture and the 75% elsewhere, Aperture's wallet share of that company is 25%.
A) Given the information above, explain how to estimate Aperture's wallet share for Acme using k-NN.
B) If k=N is chosen, the total number of training examples, what would be the effect?
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