5. Consider the case of house resale price prediction where the following information is known: Prob(x,...

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5. Consider the case of house resale price prediction where the following information is known: Prob(x, Resale Price) Lot Size (x₁) Good Schools (x₂) Crime Rate (x₂) Large Small Near Far High Low High 0.6 0.4 0.5 0.5 0.1 0.9 Resale Medium 0.3 0.7 0.3 0.7 0.4 0.6 Price Low 0.1 0.9 0.2 0.8 0.5 0.5 The decision rule for a Naïve Bayes' classifier is given by: y = arg max p(x)t = k) = arg max[p(x₁lt = k) i=1 Use the Naïve Bayes' classifier, determine the resale price of a house that is situated on a large lot size in a neighborhood with high crime rates and is not near to good schools. 5. Consider the case of house resale price prediction where the following information is known: Prob(x, Resale Price) Lot Size (x₁) Good Schools (x₂) Crime Rate (x₂) Large Small Near Far High Low High 0.6 0.4 0.5 0.5 0.1 0.9 Resale Medium 0.3 0.7 0.3 0.7 0.4 0.6 Price Low 0.1 0.9 0.2 0.8 0.5 0.5 The decision rule for a Naïve Bayes' classifier is given by: y = arg max p(x)t = k) = arg max[p(x₁lt = k) i=1 Use the Naïve Bayes' classifier, determine the resale price of a house that is situated on a large lot size in a neighborhood with high crime rates and is not near to good schools.

Answer rating: 100% (QA)

Solution We have to find Resale value when Lot size x1 large Good school x2 far Crime rate ... View the full answer