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An advertising company aims to develop a predictive model for the likelihood of purchase using a training dataset that contains hundreds of columns of demographic data, such as age, location, and income. The large dimensionality of this dataset poses a challenge for efficiently training the model. Given the absence of features representing broader groups of people, which of the following would be the most reasonable approach to reduce the dimensionality of the training data?