Feature Dropout during psl learning

[stheid]

Idea

Sometimes Features of the are not available at runtime. Hence the psl should be more robust when learning from this features in case they are unavailable, also a default score must be assigned if the feature really becomes unavailable!

An idea would be to flag features to be "potentially missing" at runtime and perhaps the psl would also be robust to those features not beeing set in the trainingdata as well.