Laurie Rech is a managoment accountant at Donnelly Bank, which has recently suffered significant loan losses. Rech and her team are worried that they do not fully understand the risk protie of thoir loans, so they would like some way of identifying loans that are likety to default. One team member suggests developing a decisio tree so that loans can be quickly and easily classified as "ikely to dotault" or "likely to repay. "After plotting and inspecting a sample of seven loans (three loans that defaulted and four loans that repaid), Rech and her team notice there are two different cuts that result in only one misplaced observation: Crecit Score = 650 and Income =$70,000. Based on this, they conclude that either would be tine to use as the first node for their decision tree. (Click the icon to viow the plot of the data.) Graph/chart Requirement 1. Are Rech and hes team correct that the two cuts are equivalent? Which one would you chose to be the first node of the decision troe? For cach potential cut, calculate the Gini impurity. Begin with the Cut 1 opton where "Credit Score =650. Start by comploting the table to show the distribution of repayments and defaulis for thes cut. Let Ri be the area above the cut (crodit tocore >650 ) and R2 the area bolow the cut (credit soore =650 Calculste the Gini impurity for R1 for the Credit Score =650 cut. You will be asked to calculate this option's Gini.jmpurity for R2, and the weighted average Gini impurity in the steps that foliow. (Enter all Gini impurity amounts as decimals to three docimal places, X XXX. Complete all input fields. Enter 0 for any zero values.) Calculate the Gini impurity for R1 for the Credit Score a 650 cut. You will be asked to calculate this option's Gini impurity for R2 and the weighted average Gini impurity in the steps that follow. (Enter all Gini impurity amounts as decimals to three decimal places, X. Complete all input fields. Enter 0 for any zero values.) Now let's look at Cut 1 option where "income =$70,000. Starf by completing the table to show the distribution of repayments and defauls for this cut. Let Rt be the area to the right of the cut (income >$70,000) and R2 the area to the left of the cut (income =570.000 area to the right of the cut (income >$70,000 ) and R2 the area to the left of the cut (income 650 ) and R2 the area bolow the cut (credit soore =650 Calculste the Gini impurity for R1 for the Credit Score =650 cut. You will be asked to calculate this option's Gini.jmpurity for R2, and the weighted average Gini impurity in the steps that foliow. (Enter all Gini impurity amounts as decimals to three docimal places, X XXX. Complete all input fields. Enter 0 for any zero values.) Calculate the Gini impurity for R1 for the Credit Score a 650 cut. You will be asked to calculate this option's Gini impurity for R2 and the weighted average Gini impurity in the steps that follow. (Enter all Gini impurity amounts as decimals to three decimal places, X. Complete all input fields. Enter 0 for any zero values.) Now let's look at Cut 1 option where "income =$70,000. Starf by completing the table to show the distribution of repayments and defauls for this cut. Let Rt be the area to the right of the cut (income >$70,000) and R2 the area to the left of the cut (income =570.000 area to the right of the cut (income >$70,000 ) and R2 the area to the left of the cut (income
