ENH optimize NMF inner loop

The call to np.maximum was taking 20% of the time.
Multiplying by Hn > 0 is about twice as fast.

This reverts commit 6ef08cfac27cda790a5d0d2dd2da82bf744905eb.
FIX max_features in CountVectorizer

Fixes #2443: max_features would be selected based on document frequency
rather than term frequency.
COSMIT pyflakes feature_extraction.text tests
DOC error in feature_extraction.text docstrings

Spotted by @madisonmay. Fixes #2486.
another speedup attempt for index.html: carousel images to use thumbnails instead, 1 blocking js removed for page (sidebar.js)
cleanup changes
remove paren
ENH: small optimization in PresortBestSplitter
add lossless image compression for docbuilding machine
switch species_kde to thumbnail
logo lossless compressions
Fix typo in the Gaussian PDF

Hopefully, this same issue doesn't exist in the code.

I would also feel more comfortable if mu_y and sigma_y were mu_iy and sigma_iy, respectively, seeing as there are separate distributions per feature, per class.
Merge pull request #2489 from samuela/patch-1

Fix typo in the Gaussian PDF in Naive Bayes docs
add coverage test for travis
coverall added
remove whitespace, fix pip install
FIX scipy API
... add the fix to import check
Merge pull request #2497 from dengemann/extend_fast_dot

FIX: support older scipy API for fast_dot
AdaBoostRegressor: fix redundant recalculation of error_vect.max()