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Answer the question for two scenarios 1. Say that a neural network based model has been constructed to predict the creditworthiness of an applicant...
Answer the question for two scenarios
1. Say that a neural network based model has been constructed to predict the creditworthiness of an applicant for approving Loan. The output of model is in range 0 to 1. With “0” meaning BAD NEWS - Loan NOT Approved and “1” meaning very Good News - Loan Approved.
· Applicant A receives a score of 0.83
· Applicant B receives a score of 0.56
· Applicant C receives a score of 0.26
As a loan approving officer, please rate the applicants under following category: High Risk, Medium Risk or Low Risk and whether you would approve their loan. Justify your answer?
2. Say that a neural network based model has been constructed to predict the cancer probability of a patient. The output of model is in range 0 to 1. With “0” meaning BAD NEWS – Patient has cancer and “1” meaning Good News – Patient is completely cancer free.
· Patient A receives a score of 0.83
· Patient B receives score of 0.56
· Patient C receives a score of 0.26
As a physician, how would rate each patient: High Risk, Medium Risk or Low Risk and which patient would you classify as having cancer. Justify your answer?
Is your answer same for both the scenario, If not Why? Explain your reasoning
