(2) In the following table, each record contains the personal information of a borrower along with a class label indicating whether the borrower has defaulted on the loan payments. Home Marital Tid Annual Defaulted Owner Status Income Borrower 1 Yes Single 125K No 2 No Married 100K No 3 No Single 70K No 4 Yes Married 120K No 5 No Divorced 95K Yes No Married 60K No 7 Yes Divorced 220K No 8 No Single 85K Yes 9 No Married 75K No 10 No Single 90K Yes 6 Consider the problem of predicting whether a loan application will repay his/her loan obligations or become delinquent, subsequently defaulting on his/her loan. (a) Can you design a decision tree based on the data in the above table? (b) Can you briefly explain the reason why do you choose attributes in your decision tree that was constructed in part (a)? (2) In the following table, each record contains the personal information of a borrower along with a class label indicating whether the borrower has defaulted on the loan payments. Home Marital Tid Annual Defaulted Owner Status Income Borrower 1 Yes Single 125K No 2 No Married 100K No 3 No Single 70K No 4 Yes Married 120K No 5 No Divorced 95K Yes No Married 60K No 7 Yes Divorced 220K No 8 No Single 85K Yes 9 No Married 75K No 10 No Single 90K Yes 6 Consider the problem of predicting whether a loan application will repay his/her loan obligations or become delinquent, subsequently defaulting on his/her loan. (a) Can you design a decision tree based on the data in the above table? (b) Can you briefly explain the reason why do you choose attributes in your decision tree that was constructed in part (a)