Question about feature selection when a feature is made up of multiple features


How should one handle feature selection (for predictors) when you have a feature, say revenue retention (%) that is made of other features including, upgrades(), downgrades (), cancellations($), etc. Should I use either the revenue retention and discard the rest (since they are all in the calculation of revenue retention). Does it make sense to include all 3 features (upgrades, downgrades, cancellations) AND also revenue retention in the model?


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