Topic 1 Question 269
You are developing a model to help your company create more targeted online advertising campaigns. You need to create a dataset that you will use to train the model. You want to avoid creating or reinforcing unfair bias in the model. What should you do?
Include a comprehensive set of demographic features
Include only the demographic groups that most frequently interact with advertisements
Collect a random sample of production traffic to build the training dataset
Collect a stratified sample of production traffic to build the training dataset
Conduct fairness tests across sensitive categories and demographics on the trained model
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- 正解だと思う選択肢: D
D. Stratified Sampling: Randomly sampling your data might not accurately represent the diversity of your target audience, potentially introducing bias by over- or under-representing certain demographics. Stratified sampling ensures your training dataset reflects the distribution of sensitive features (e.g., age, gender, income) observed in your production traffic, helping mitigate bias during model training.
E. Fairness Testing: Simply collecting unbiased data isn't enough. Regularly testing your trained model for fairness across sensitive categories is crucial. This involves measuring and analyzing metrics like accuracy, precision, recall, and F1 score for different demographic groups. Identifying disparities in performance can trigger further investigation and potential re-training to address bias.
👍 1pikachu0072024/01/13
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