Nonlinear methods can result in a smaller (lower-dimensional) representation, but they are non-linear so they are harder to use and usually require more data. O

Nonlinear methods can result in a smaller (lower-dimensional) representation, but they are non-linear so they are harder to use and usually require more data. On the other hand, PCA is easy and having 50 or more principal components is often not a problem, unless you are doing visualization. With the additional representational capacity from just keeping extra dimensions you can still get good reconstructions.