Design, implement and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program's discipline. Total Mark: 15 This assignment considers the following hypothetical scenario. A real estate agency would like to use artificial intelligence to better predict whether a certain customer will buy a specific house, so they can focus their efforts on promising potential sales, Specifically, they want to label pairs of customers and houses according to whether they belong to the target class buys or not. The agency has selected seven attributes, each taking values from {yes,no}, namely - Basic features of the house: garden: whether the house has a garden or not - parking: whether the house has private parking or not - good_nbhood: whether the house is in a good neighborhood or not expensive: whether the house is expensive or not - characteristics of the client: young: whether the client is young or not rich: whether the client is rich or not interested: whether the client is interested in the house or not They also have some preliminary ideas about the kind of model they are interested in and have collected a small dataset for machine learning. Your task is to help them understand their options better and to recommend next steps towards realizing their goal, by answering the following questions: Question 1 The agency is interested in Narve Bayes model using the three attributes expensive, interested and rich. Given the training data in Table 1 use your Knowledge on Naive Bayes classifier to predict the class for the data in testing data in Table 2. (1.2: 5 Marks) Qurstion 2 Elaned on a critical asorimme of the Nave Unay model considered above. Anruct the followne curition a) Evalaxte yeur Narue Bryei modeli from Qaritions I by calculating the actacy co the teit data provided in Tale 2. (2.4: 1. Marka) (1.2. 2 starls) i. fu the Narie lisyei model a pood theice to sohve thin problere? ii If yes, nher. ii. If no, uthy not, and what can we de he enhancer than model? Tolke 21