Sample weights for gradient boosting

Exponential loss for classification + predict_proba refactoring
more tests
add exponential loss to narrative documentation
cosmit: doc
raise ValueError for sample_weights and robust regression
bincount supports weights
more elegant PriorProbabilityEstimator
adressed Olivier's feedback
update tests for new exception types
sample weight support for robust regression via weighted percentile algo
fix: consider sample_weights in robost init estimator and negative_gradient
fix: add **kwargs to Multinomial loss' negative_gradient
more tests for weighted percentile
cosmit
add GBRT sample weights to whats new
fix: sample_weight is None in Huber.deviance
fix: sample_weight multiplication in Huber leaf updates
more tests (non-uniform weights, weight consistency and invariance to scaling, deviance consistence)
cosmit arr -> array
non-uniform weight test case for both reg and clf and all losses
add probability output for exponential loss
we can produce probabilistic outputs using exponential loss
Merge pull request #3224 from pprett/gbrt-sample-weight

[MRG+2] Sample weights for gradient boosting