ENH Nystroem kernel approxmation
ENH renamed class NystromKernelApproximation to Nystrom (it is in the kernel_approximation module). Also improvements to example docstring
DOC docstrings for Nystroem.
ENH cosmit, gamma defaults do None, not 0. address some of @mblondel's comments.
ENH tests for Nystrom, check that n_components is smaller than n_samples.
DOC added note in example that digits data is to small.
DOC narrative doc for Nystroem.
DOC updated whatsnew with Nystroem.
FIX: Do not rely on strides for contiguous arrays

When an array is contiguous in memory but has `shape[dim] == 1`, then
its `strides[dim]` is not really used, so it can be considered arbitrary
even if the array is contiguous. This is generally true for 0-sized arrays.

If there is no chance of 0-sized (or 1-sized and 1-dimensioal) arrays, then
this code is perfectly correct in current numpy. But its a dangerous
design choice and it would be nice to be able to change numpy at some point.
ENH: use broadcasting, not tile

It's faster and doesn't change anything
ENH don't import * in utils __init__.py
cosmit: remove fourth quote
Call DecisionTreeRegressor instead of Tree
COSMIT Remove duplicated assignement
Use the check_input argument
DOC : add description of check_input args
DOC explain parameter estimators_
DOC explain parameter estimators_ (2)
ENH Move parameter checking to fit
COSMIT