Can PCA be used for regression-based problem statements? If Yes, then explain the scenario where we can use it

Data Science, AI and ML
#1

Yes, we can use Principal Components for regression problem statements.

PCA would perform well in cases when the first few Principal Components are sufficient to capture most of the variation in the independent variables as well as the relationship with the dependent variable.

The only problem with this approach is that the new reduced set of features would be modeled by ignoring the dependent variable Y when applying a PCA and while these features may do a good overall job of explaining the variation in X, the model will perform poorly if these variables don’t explain the variation in Y.