And it turns out that if you're retaining 99% of the variance or 95% of the variance or whatever, it turns out that just using regularization will often give you at least as good a method for preventing over-fitting and regularization will often just work better, because when you are applying linear regression or logistic regression or some other method with regularization, well, this minimization problem actually knows what the values of y are, and so is less likely to throw away some valuable information, whereas 