You are tasked with building a predictive model aws video

machine-learning video for you are tasked with building a predictive model for customer lifetime value (CLV) using Amazon SageMaker. Given the complexity of the

Full Certification Question

You are tasked with building a predictive model for customer lifetime value (CLV) using Amazon SageMaker. Given the complexity of the model, it’s crucial to optimize hyperparameters to achieve the best possible performance. You decide to use SageMaker’s automatic model tuning (hyperparameter optimization) with Random Search strategy to fine-tune the model. You have a large dataset, and the tuning job involves several hyperparameters, including the learning rate, batch size, and dropout rate. During the tuning process, you observe that some of the trials are not converging effectively, and the results are not as expected. You suspect that the hyperparameter ranges or the strategy you are using may need adjustment. Which of the following approaches is MOST LIKELY to improve the effectiveness of the hyperparameter tuning process?