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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

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 Naïve Bayes model using the three attributes expensive, interested and rich. Given the training data in Table 1 use your Knowledge on Naïve Bayes classifier to predict the class for the data in testing data in Table 2.

Table 1: 

Table 1: 123456789 10 11 1234598 CISI 16 17 garden good nbhood parking expensive yes no yes yes yes no Do no yes yes no yes 12 yes 13 yes 14 yes yes no no yes yes yes yes no yes 19 no 20 no yes yes no no yes no yes yes no yes yes yes yes no yes no yes no no no yes yes no no no yes yes no yes no no no no no yes yes yes no yes no yes no yes no yes yes yes no no no yes no yes no no interested no yes yes yes yes no yes no no yes no no yes yes no yes yes no yes yes young yes yes yes yes no no yes yes yes yes yes yes yes no yes yes yes yes no yes rich yes yes no no no no no no no yes no yes yes no buys no no no no no no no no yes no no no yes yes yes no yes yes yes no yes yes no yes no no

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