Preliminary implementation of scoreForEval for Logistic Regression

Note: Also changed predictPoint to return predicted probability instead of
the predicted label, i.e. removed the round(..)
This should be fixed.
Added predictScore and score functions to HeneralizedLinearAlgorithm.scala

For classification models, usually one first calculates scores and then bases labels on the scores.
Currently, the scores are not accessible.
I generalized this concept and made it more of a two stage approach,
since the scores are interesting in their own right.

However, since this is only useful for classification models, the
GeneralizedLinearAlgorithm.scala is more bloated than it needs to be.
Maybe it is better to implement these methods only for subclasses that
actually benefit from these scores.
Make the score functionality specific to only LogisticRegression and SVM:

Instead of having a more abstract score and predict, score now only works
for SVM and LR, since it seems more natural
Working ROC AUC
Implemented Avg Precision, updated Docs
Sample dataset for logistic regression

True underlying process:
beta_0 = 0.5
beta_1 = 2.0
beta_2 = 0.2

with correlated features