11-22 Gini impurity. Laurie Rech is a management 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 profile of their loans, so they would like some way of identifying loans that are likely to default. One team member suggests developing a decision tree so that loans can be quickly and easily classified as "likely to default" 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: Credit Score = 650 and Income = $70,000. Based on this, they conclude that either would be fine to use as the first node for their decision tree. Repay Default Credit Score 750 700 650 600 550 500 55 60 65 70 75 80 85 90 Annual Income ($000s) 1. Are Rech and her team correct that the two cuts are equivalent? Which one would you choose to be the first node of the decision tree? 2. Why might Rech care about Gini impurities when making decisions?
11-22 Gini impurity. Laurie Rech is a management 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 profile of their loans, so they would like some way of identifying loans that are likely to default. One team member suggests developing a decision tree so that loans can be quickly and easily classified as "likely to default" 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: Credit Score = 650 and Income = $70,000. Based on this, they conclude that either would be fine to use as the first node for their decision tree. Repay Default Credit Score 750 700 650 600 550 500 55 60 65 70 75 80 85 90 Annual Income ($000s) 1. Are Rech and her team correct that the two cuts are equivalent? Which one would you choose to be the first node of the decision tree? 2. Why might Rech care about Gini impurities when making decisions?
Chapter1: Making Economics Decisions
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Transcribed Image Text:11-22 Gini impurity. Laurie Rech is a management 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
profile of their loans, so they would like some way of identifying loans that are likely to default. One team
member suggests developing a decision tree so that loans can be quickly and easily classified as "likely to
default" 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:
Credit Score = 650 and Income = $70,000. Based on this, they conclude that either would be fine to use as
the first node for their decision tree.
• Repay • Default
750
700
650
600
550
500
55
80
85
Annual Income (S000s)
60
65 70 75
90
1. Are Rech and her team correct that the two cuts are equivalent? Which one would you choose to be
the first node of the decision tree?
2. Why might Rech care about Gini impurities when making decisions?
Credit Score
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