In the context of supervised learning, that can be also what you go feature selection or basically selecting the predictive features. So like if we went back to my house example, maybe I was feeding like the length of the driveway and the number of trees in the yard. And it might turn out that neither of those have any effect on house prices. We can reduce it to a smaller problem by having this whole PCA go look, those don't matter, throw that part out. It's really about the number of bathrooms and the square footage or something.