2. Nearest Neighbors for Predictive Modeling Assume you run a new start-up media that provides subscription-based streaming services to its customers. Your goal is to predict whether a new customer will respond to an offer of the streaming services based on how other similar customers have responded. Table 6-1 shows the five existing customers you previously have contacted with the service offer. For each of them you have their name, age, income, residential status, years at current address, and whether they responded to the offer. NB: Use the example in the textbook to answer the question. Table 6-1 Customer Age Income Residential Years at Response (1000s) status current (Target) address Alex 35 52 ? Mike 44 Mary 120 12 Robert 150 Nick 30 45 yes Residential status: 1-owner, 2= renter, 3= other 3 5 33 58 55 yes yes 2 1 1 1 1 2 no 60 20 2 1 no Ruth 29 Question: 2.1 Will the new customer, Alex, respond Yes to the offer? Show your work. 2.2 Based on your answer to 2.1, what is the average score for Alex to respond Yes if we score for the Yes class, so that Yes=1 and No=0? W