In the context of preparing a dataset for machine learning, you are conducting Exploratory Data Analysis (EDA) and encounter missing values across several features. The dataset is large, and the missing values are randomly distributed. Cost efficiency and scalability are key considerations for your project. Which of the following methods is MOST appropriate for addressing missing data under these constraints? Choose the BEST option.