Considering the training set data presented in Annex 1, perform the following tasks:

1. Build a decision tree based on the training set data, using the algorithm provided in the lecture, considering all attributes as possible classification attributes, and as attribute selection method use the information gain.

2. Apply the nave Bayesian classification on the training data set in Annex 1, and classify this new data Senior person with job, doesnt own a house and has good credit rating with both the Bayesian classifier as well as the decision tree obtained in a).

Age	Has job	Owns house	Credit rating	Approve loan
Young	False	False	Fair	No
Young	False	False	Good	No
Young	True	False	Good	Yes
Young	True	True	Fair	Yes
Young	False	False	Fair	No
Middle	False	False	Fair	No
Middle	False	False	Good	No
Middle	True	True	Good	Yes
Middle	False	True	Excellent	Yes
Middle	False	True	Excellent	Yes
Old	False	True	Excellent	Yes
Old	False	True	Good	Yes
Old	True	False	Good	Yes
Old	True	False	Excellent	Yes
Old	False	False	Fair	No