sbo 0.5.0

Former kgram_freqs class is now called sbo_kgram_freqs. The constructor
kgram_freqs() is still available as an alias to sbo_kgram_freqs().

Former sbo_preds class is now substituted by two classes:

  - `sbo_predictor`: for interactive use
  - `sbo_predtable`: for storing text predictors out of memory (e.g. 
  `save()` to file)

sbo_predictor and sbo_predtable objects are obtained by the homonym
constructors, which are now S3 generics accepting character input, as well as
sbo_kgram_freqs and sbo_predtable (for the sbo_predictor() constructor)
class objects. In particular, these allow to directly train a text predictor
without storing the intermediate sbo_dictionary, and kgram_freqs objects.
The behaviour of the dict argument in kgram_freqs() and kgram_freqs_fast() has changed, now accepting either a sbo_dictionary, a character or a formula (see also 'New features').
The sbo_predictor implementation dramatically improves the speed of
predict() (by a factor of x10). A single call to predict() now allocates a
few kBs of RAM (whereas it previously allocated few MBs, c.f. issue #10).
Metadata of sbo_kgram_freqs and sbo_pred* objects is now stored via
attributes (#11).

New S3 class sbo_dictionary.
New S3 class word_coverage with generic constructors and a preconfigured
plot() method.
Dictionaries in kgram_freqs() and sbo_pred*() can now
be built also with a fixed target coverage fraction of training corpus.
Added prune() generic function for reducing -gram order of
kgram_freqs and sbo_predtable's.
Added summary() methods for sbo_kgram_freqs and sbo_pred* objects;
correspondingly, the output of print() has been simplified considerably (#5).
The object of class sbo_kgram_freqs, sbo_dictionary, sbo_predictor and
sbo_predtable can be constructed either through the homonymous constructors,
or through the aliases kgram_freqs(), dictionary(), predictor(),
predtable().

sbo now has SystemRequirements: C++11, for correct integration with C++11 code (in particular std::unordered_map).
Model training (with sbo_predictor()) is now considerably faster, due to
optimizations in the algorithm for building Stupid Back-Off prediction tables.
The Stupid Back-Off algorithm is now thoroughly tested, and small
inconsistencies between the predict.kgram_freqs() and
predict.sbo_predictor() methods have been fixed, including:
```
  - Proper handling of unknown words
  - Consistent handling of ties in prediction probabilities.
```
Model evaluation in eval_sbo_predictor() is now carried out by sampling
a single sentence from each document in test corpus.
Removed unnecessary dependencies from Depends and Imports package fields.

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