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You are a data scientist at an e-commerce company developing a product recommendation model using Amazon SageMaker. After the initial training, you want to improve model performance through better hyperparameters and possibly different algorithms. Additionally, you need to ensure the model is not biased toward any product category and generalizes well to new data. Which strategy is MOST likely to improve the model’s performance and ensure fairness?