[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 so the label preceeds the docs... not after. That may explain some
things. Silly mistake


On Wed, Aug 13, 2014 at 4:43 AM, Olivier Grisel <notifications@github.com>
wrote:

> In doc/modules/decomposition.rst:
>
> > @@ -59,6 +58,38 @@ data based on the amount of variance it explains. As such it implements a
> >
> >  .. _RandomizedPCA:
>
> This should be moved below the IncrementalPCA section and replaced by a
> new _IncrementalPCA label instead.
>
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> <https://github.com/scikit-learn/scikit-learn/pull/3285/files#r16166135>.
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