MLS-C01 · Question #255
A company has hired a data scientist to create a loan risk model. The dataset contains loan amounts and variables such as loan type, region, and other demographic variables. The data scientist wants…
The correct answer is D. Jensen-Shannon divergence E. Kullback-Leibler divergence F. Total variation distance. https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-measure-data-bias.html
Question
A company has hired a data scientist to create a loan risk model. The dataset contains loan amounts and variables such as loan type, region, and other demographic variables. The data scientist wants to use Amazon SageMaker to test bias regarding the loan amount distribution with respect to some of these categorical variables. Which pretraining bias metrics should the data scientist use to check the bias distribution? (Choose three.)
Options
- AClass imbalance
- BConditional demographic disparity
- CDifference in proportions of labels
- DJensen-Shannon divergence
- EKullback-Leibler divergence
- FTotal variation distance
How the community answered
(39 responses)- A18% (7)
- B3% (1)
- C8% (3)
- D72% (28)
Explanation
https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-measure-data-bias.html
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