Uh , they 're good because you  you  you learn to distinguish between these categories that you want to be good at distinguishing between. And PCA doesn't do that. It  PAC - PCA  low - order PCA throws away pieces that are uh , maybe not  not gonna be helpful just because they 're small , basically.
Right.
But , uh , the problem is , training sets aren't perfect and testing sets are different. So you f you  you face the potential problem with discriminative stuff , be it LDA or neural nets , that you are training to discriminate between categories in one space but what you 're really gonna be g getting is  is something else.
Uh - huh.