Question 75 of 280
Single answerYou work at a subscription-based company. You have trained an ensemble of trees and neural networks to predict
customer churn, which is the likelihood that customers will not renew their yearly subscription. The average
prediction is a 15% churn rate, but for a particular customer the model predicts that they are 70% likely to churn.
The customer has a product usage history of 30%, is located in New York City, and became a customer in 1997. You
need to explain the difference between the actual prediction, a 70% churn rate, and the average prediction. You
want to use Vertex Explainable AI. What should you do?
ATrain local surrogate models to explain individual predictions.
✓BConfigure sampled Shapley explanations on Vertex Explainable AI.
CConfigure integrated gradients explanations on Vertex Explainable AI.
DMeasure the effect of each feature as the weight of the feature multiplied by the feature value.
✓
Correct Answer: B
Configure sampled Shapley explanations on Vertex Explainable AI.
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Explanation
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