ENH speed up logistic_sigmoid (using less code)

Timings, before:

>>> x = np.linspace(-1000, 1000, 10000)
>>> %timeit logistic_sigmoid(x)
1000 loops, best of 3: 570 us per loop

After:

>>> %timeit logistic_sigmoid(x)
1000 loops, best of 3: 286 us per loop

For comparison:

>>> %timeit np.tanh(x)
10000 loops, best of 3: 117 us per loop
>>> %timeit .5 * (1 + np.tanh(x/2.))
1000 loops, best of 3: 301 us per loop

TODO: optimize log_logistic_sigmoid.
Rename cv_scores(_) back to grid_scores(_) to keep the name free for a future refactoring
Merge pull request #2299 from ogrisel/grid-scores

Rename cv_scores(_) back to grid_scores(_) to keep the name free
MISC: fix plot_multilabel example
FIX make BaseSGDClassifier an ABC
Merge pull request #2295 from larsmans/fast-sigmoid

[MRG] speed up logistic_sigmoid (using less code)
BUG: type->dtype in a cross-platform way
compute offset in a cross-platform way
BUG: don't subtract offset in binary_tree
add explicit types to neighbors cython code
ENH/FIX: improve logcosh function + tests
FIX/ENH: revert changes, improve doc
FIX: 80 characters
COSMITS
COSMITS
COSMITS