Topic 1 Question 88
You are an ML engineer at a bank. You have developed a binary classification model using AutoML Tables to predict whether a customer will make loan payments on time. The output is used to approve or reject loan requests. One customer’s loan request has been rejected by your model, and the bank’s risks department is asking you to provide the reasons that contributed to the model’s decision. What should you do?
Use local feature importance from the predictions.
Use the correlation with target values in the data summary page.
Use the feature importance percentages in the model evaluation page.
Vary features independently to identify the threshold per feature that changes the classification.
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コメント(12)
- 正解だと思う選択肢: A
To access local feature importance in AutoML Tables, you can use the "Explain" feature, which shows the contribution of each feature to the prediction for a specific example. This will help you identify the most important features that contributed to the loan request being rejected.
Option B, using the correlation with target values in the data summary page, may not provide the most accurate explanation as it looks at the overall correlation between the features and target variable, rather than the contribution of each feature to a specific prediction.
Option C, using the feature importance percentages in the model evaluation page, may not provide a sufficient explanation for the specific prediction, as it shows the importance of each feature across all predictions, rather than for a specific prediction.
Option D, varying features independently to identify the threshold per feature that changes the classification, is not recommended as it can be time-consuming and does not provide a clear explanation for why the loan request was rejected
👍 6shankalman7172023/02/23 - 正解だと思う選択肢: A
Agree with A. "Local feature importance gives you visibility into how the individual features in a specific prediction request affected the resulting prediction. Each local feature importance value shows only how much the feature affected the prediction for that row. To understand the overall behavior of the model, use model feature importance." https://cloud.google.com/automl-tables/docs/explain#local
👍 4mil_spyro2022/12/17 - 正解だと思う選択肢: A
Local, not global since they asked about one specific prediction. Check out that section on this blog: https://cloud.google.com/blog/products/ai-machine-learning/explaining-model-predictions-structured-data/ Cool stuff!
👍 4JamesDoe2023/03/28
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