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Dimensionality Reduction - What is the difference between PCA and LDA?


PCA is an unsupervised method that aims to find the directions of maximum variance in the data, while LDA is a supervised method that aims to find the projection that best separates the classes in the data. The choice of method depends on the specific problem and the characteristics of the dataset.