Fixes ovr in the binary classifier case, and adds support for lists of feature arrays in the multiclass case.
Added make_fit_parameter method
dded tests to test_boosting
Added _check_sample_weight
Shifted the _check_sample_weight into BaseWeightBoosting class
GradientBoostingClassifier docstring incorrectly specified default for max_features as "auto" when it is None.
Merge pull request #3715 from trevorstephens/correct-gbc-docstring

GradientBoostingClassifier docstring correction
Merge pull request #3713 from akshayah3/Boost

More explicit error message in Adaboost
DOC Add solido testimonial

Fixes #3668.
FIX ovr predict_proba in the binary case

Previous commit fixed the shape, but swapped the actual probabilities.
Merge branch 'pr/3710'
Raise exception for sparse inputs in the case of svd solver

Fixes #3709, #3718.
Rename k to n_clusters in docs
Merge pull request #3724 from mlopezantequera/patch-1

Rename k to n_clusters in docs
MAINT use Python versions provided by AppVeyor CI
FIX call srand whenever random_seed >= 0 in libsvm

This bug was discovered by #3691 (failing test under windows).
Enable grid search with classifiers that may throw an error on individual fits.
Fix sparse_cg solver when max_iter is specified.
Merge pull request #3730 from ogrisel/fix-libsvm-random-seed

[MRG+1] FIX call srand whenever random_seed >= 0 in libsvm
MAINT missing numpy / scipy for the Python 3.3 build

Building scikit-learn on Python 3.3 on appveyor would first require
building numpy and scipy wheels.

Disabling in the mean time.