[SPARK-4486][MLLIB] Improve GradientBoosting APIs and doc

There are some inconsistencies in the gradient boosting APIs. The target is a general boosting meta-algorithm, but the implementation is attached to trees. This was partially due to the delay of SPARK-1856. But for the 1.2 release, we should make the APIs consistent.

1. WeightedEnsembleModel -> private[tree] TreeEnsembleModel and renamed members accordingly.
1. GradientBoosting -> GradientBoostedTrees
1. Add RandomForestModel and GradientBoostedTreesModel and hide CombiningStrategy
1. Slightly refactored TreeEnsembleModel (Vote takes weights into consideration.)
1. Remove `trainClassifier` and `trainRegressor` from `GradientBoostedTrees` because they are the same as `train`
1. Rename class `train` method to `run` because it hides the static methods with the same name in Java. Deprecated `DecisionTree.train` class method.
1. Simplify BoostingStrategy and make sure the input strategy is not modified. Users should put algo and numClasses in treeStrategy. We create ensembleStrategy inside boosting.
1. Fix a bug in GradientBoostedTreesSuite with AbsoluteError
1. doc updates

@manishamde @jkbradley
@manishamde The current explanation is correct for the original Gradient Boosting algorithm, which uses weak hypothesis weights and is oblivious to the weak learner being used.  Your suggested explanation is really for TreeBoost, Friedman's improvement to the original algorithm which is specialized for trees (which we should add at some point but isn't what we're claiming to have now, I'd say).