In the context of preparing a large dataset for machine learning, you are tasked with reducing its dimensionality to improve model performance and reduce computational costs. The dataset contains hundreds of features, some of which are highly correlated. Given the constraints of needing to preserve as much of the original variability as possible and the requirement to facilitate easier data visualization, which of the following techniques would be the MOST appropriate to achieve these goals? Choose one correct option.