MLS-C01 Question 237
Select 4A retail company uses machine learning to recommend products to its customers. They want to evaluate the performance of a new recommendation model compared to their current production model. They decide to conduct an online evaluation using A/B testing. Which of the following are essential steps to correctly set up and analyze the A/B test?
- A
Split traffic between the new model and current model based on pre-defined percentages (e.g., 50% each).
- B
Ensure customers are randomly assigned to either the new model or the current model, and the assignment remains consistent throughout the test.
- C
Use the same evaluation metric (e.g., click-through rate) for both models to compare their performance.
- D
Immediately switch all traffic to the new model if it shows slightly better performance after a few hours of testing.
- E
Monitor statistical significance of the results before deciding which model performs better.
Show answer and explanation
Correct answers: A, B, C, E
Explanation
A/B testing involves splitting traffic between the models, ensuring consistent and random assignment, using comparable metrics, and validating results statistically to make informed decisions. This process avoids premature conclusions and ensures that the new model is a true improvement before switching traffic.
- A. Correct.
Splitting traffic ensures that both models are exposed to a representative subset of users, allowing a fair comparison.
- B. Correct.
Random and consistent assignment prevents biases and ensures that the results are not skewed by user behavior changes.
- C. Correct.
Using the same evaluation metric ensures a meaningful comparison between the two models' performance.
- D. Incorrect.
Switching all traffic immediately based on slight initial results can lead to premature decisions and ignores statistical significance.
- E. Correct.
Monitoring statistical significance ensures that performance differences are not due to random chance but are instead reliable indicators of model performance.