sampler addded with tests cases and documentation.

Added support for kernels: 
 * Radial Basis Function Kernel (RBFSampler)
 * Additive Chi Squared Kernel (AdditiveChi2Sampler)
 * Skewed Chi Squared Kernel (SkewedChi2Sampler)
I like the idea behind trying to turn `xtest` and `xtrain` back into sparse matrices, but I'm not sure if it's necessary, because the main reason we want to use sparse is for cases where the data set won't fit into memory at all when it's dense, so if `fit_transform` didn't run out of memory, we're probably okay.

And because this is Python, it's possible/likely that the old dense version won't get garbage collected right away, so making a sparse copy of the matrix will actually probably use more memory in the long run.

Anyway, my point is, you can remove all of your calls to `csr_matrix`.