Questions
BA 3551 (002 & 003) Exam 2
Single choice
Assume you work for a large real estate company, and you are required to build a prediction model to predict the listing prices for houses that are being putting up for sale. You have an existing dataset with 5 houses and their prices, and you are trying to predict the listing price for house Z. You decide to train a k-NN model. Below, you have the normalized version of the data. HOUSE Number bedrooms Number bathrooms Patio PRICE A 1 1 1 $650,000 B 1 1 0 $610,000 C 0.5 0 1 $620,000 D 0 0.5 0 $550,000 E 0 0 0 $540,000 Z 0.5 1 1 ??? Additionally, you have the Euclidian distances between the existing houses and the new house, Z. A-Z 0.5 B-Z 1.12 C-Z 1 D-Z 1.52 E-Z 1.23 Assume you run a k-NN model. You set k = 4. What would be the price predicted for house Z?
Options
A.$607,500
B.$605,000
C.$594,000
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Step-by-Step Analysis
To solve this, we need to apply a k-NN prediction with k = 4 using the given normalized features and the prices of the five existing houses.
First, identify the four closest neighbors to house Z by Euclidean distance. The distances are: A-Z = 0.5, B-Z = 1.12, C-Z = 1.00, D-Z = 1.52, E-Z = 1.23. Ordering from smallest to largest, the four nearest are A (0.5),......Login to view full explanationLog in for full answers
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