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CT-AI · Question #19
CT-AI Question #19: Real Exam Question with Answer & Explanation
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Question
A bank wants to use an algorithm to determine which applicants should be given a loan. The bank hires a data scientist to construct a logistic regression model to predict whether the applicant will repay the loan or not. The bank has enough data on past customers to randomly split the data into a training data set and a test/validation data set. A logistic regression model is constructed on the training data set using the following independent variables: Gender Marital status Number of dependents Education Income Loan amount Loan term Credit score The model reveals that those with higher credit scores and larger total incomes are more likely to repay their loans. The data scientist has suggested that there might be bias present in the model based on previous models created for other banks. Given this information, what is the best test approach to check for potential bias in the model?
Options
- AExperienced-based testing should be used to confirm that the training data set is operationally
- BBack-to-back testing should be used to compare the model created using the training data set to
- CAcceptance testing should be used to make sure the algorithm is suitable for the customer. The
- DA/B testing should be used to verify that the test data set does not detect any bias that might have
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