[MRG] Incremental PCA

An implementation of Incremental PCA. See [Incremental Learning for Visual Tracking, J. Lim, D. Ross, R. Lin, M. Yang, 2004](http://www.cs.toronto.edu/~dross/ivt/LimRossLinYang_nips04.pdf) for more details.

The key idea behind this PR is to have an out-of-core PCA that gives roughly equivalent results while using constant memory (on the order of the ```batch_size``` rather than ```n_samples```).
Ah yes, thanks for the clarification. As far as I can see it is not mentioned as such in `PCA`, though. `PCA` does not have `y=None` in `transform`, only in `fit`, which seems to be the way things are handled in general (side note: causing PLS, which transforms both sides, not to work with the pipeline. But that is a completely different matter :))