Question 1 of 30
A data scientist is tasked with developing a predictive model using Azure Machine Learning service to forecast sales for a retail company. The dataset includes various features such as historical sales data, promotional activities, and economic indicators. After preprocessing the data, the data scientist decides to use a regression algorithm. Which of the following steps should be prioritized to ensure the model\'s performance is optimized before deployment?
Conduct hyperparameter tuning to find the optimal settings for the regression algorithm.
Increase the size of the dataset by duplicating existing records to enhance model training.
Use a single evaluation metric to assess the model's performance.
Implement a complex ensemble method without understanding the base algorithms.

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