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Dimensionality reduction refers to techniques for reducing many variables into a smaller number while keeping as much information as possible. One prominent method is [tag pca]

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Can we use feature selection and dimensionality reduction together?

Every time you compress the feature space you are losing some information. The original feature engineering stage you outlined sounds like a meaningful compression & might make sense in the context of …
Oliver Foster's user avatar