FIX wording in whats new in 0.15.1
FIX six issue with module imports

Fixes #3518, #3519.

Inspired by Johannes Schönberger's patch to scikit-image,
https://github.com/scikit-image/scikit-image/commit/71743d2d6ff3666c9530278dfd650c2435fa15d9
FIX only use testing.ignore_warnings in tests
MAINT: be robust to numpy's DeprecationWarning

numpy 1.9 raises a lot of 'VisibleDeprecationWarning', which breaks our
test suite
BUG: n_samples instead of n_features in cd_fast

Was causing a segfault under numpy master, that is more sensitive to
array index overflow. Our code was wrong, numpy is not to be blamed.

Conflicts:
	sklearn/linear_model/cd_fast.c
FIX #3566: redefine isfinite alias in sklearn

npy_isfinite from npy_math.h depends on the compiler used to build
numpy. If we build scikit-learn with a different compiler (e.g. MSVC
vs MinGW) this can cause link errors.

Therefore we redefine the isfinite macro in a scikit-learn specific header
file.
FIX bump up the miniconda installation script
fix typo (on -> one)
DOC double backticks for fixed-width (code) font

Fixes #3337. Also other minor fixes while I was at it.
FIX Gaussian KDE should return array, not scalar

Fixes #3269.
COSMIT use explicit RandomState in KDE tests
DOC optimize some PNG images, shaves off 24kB
Fix grammar

it's should be its
DOC: write cost function of logistic regression.

I feel it important to state clearly what is the cost function of the
model because:

    * Some might want to compare their implementation against this one,
    in which case it is important to know exactly what is the form of the
    cost function

    * Furthermore since the models are quite inconsistent in terms of
    notation for the regularization parameter: some models in this
    module penalize by 1/C, others by alpha and others by alpha/2
fixed typo: diriclet -> dirichlet
Fix labels of inliers vs outliers

At least based on what svm.OneClassSVM does in the example linked from this document, the description was wrong; labels actually assigned are 1/-1 for good/bad respectively, not 0/1.
DOC adding return type and improving module doc
DOC numpydoc convention for Bunch-returning functions

Also cap lines at 80 chars, remove trailing spaces.

As suggested by @jnothman at
https://github.com/scikit-learn/scikit-learn/pull/3316/files#r14269818
FIX MinMaxScaler behavior on 1D inputs.
Lift division out of loop in _isotonic_regression.

I'm surprised the C compiler doesn't do this, but it seems
to make a difference in the benchmarks.

Conflicts:
	sklearn/_isotonic.c