Add information on where to get data from.
"Slight" refactoring.

Move everything related to using ES purely as NoSQL backend into its own package
and only keep whatever is more general in the top level package. The goal is to
facilitate using the termvector entpoint of ES for input in a second approach.
Add slf4j log4j logging endpoint.
Enable termvector storage for example index.
Ignore any training data on TL directory
Remaining refactoring in tests.
Disable looking at tags for classification for now.
Second approach to using ES for input.

Uses the ES termvectors query to retrieve the pre-analysed/tokenised vectors of
ES as input to the Mahout feature vector encoder. With the current encoding all
term vectors need to be transferred to a central node that trains the logistic
regression model. Wondering whether this could somehow be done in parallel on
each node - combining the models afterwards...