Clarify learning interfaces

* Make threshold mandatory
Currently, the output of ``predict`` for an example is either the score
or the class. This side-effect is caused by ``clearThreshold``. To
clarify that behaviour three different types of predict (predictScore,
predictClass, predictProbabilty) were introduced; the threshold is not
longer optional.

* Clarify classification interfaces
Currently, some functionality is spreaded over multiple models.
In order to clarify the structure and simplify the implementation of
more complex models (like multinomial logistic regression), two new
classes are introduced:
- BinaryClassificationModel: for all models that derives a binary
classification from a single weight vector. Comprises the tresholding
functionality to derive a prediction from a score. It basically captures
SVMModel and LogisticRegressionModel.
- ProbabilitistClassificaitonModel: This trait defines the interface for
models that return a calibrated confidence score (aka probability).

* Misc
- some renaming
- add test for probabilistic output