Changes in 2.0.0:
 - Shadow importance.
 - Roxygen documentation.
 - Model merging for parallel, batch and deeply traceable training.
 - Fixed a minor error in leaf score calculation (basically redundant
 to the model performance). Thanks to Mateusz Fedoryszak for spotting
 this.
 - Fixed OOB predictions returned by predict(), which are now always
 data.frame, even in the multi-label case.

Changes in 1.1.0:
 - Code portability fixes.
 - predict method returns OOB results for no input data even when fern
 forest is not saved.
 - Fixed minor importance calculation bug.

Changes in 1.0.0:
 - Published in JSS.

Changes in 0.3.3:
 - Fixed uninitialised memory bug causing problems with LLVM.

Changes in 0.3.2:
 - Prototype of a multi-label classification.
 - Removed redundant constant from scores definition; score values will
 be different, but the importance scores and prediction results will be
 the same as generated by previous versions.

Changes in 0.3.1:
 - predict method for rFerns returns OOB votes/scores when no predictors
 are given.

Changes in 0.3:
 - Handling of unbalanced classes.
 - Performance tweaks.

Changes in 0.2:
 - Added support for integer and ordered-factor attributes, suggested by
 Bill Venables.

Changes in 0.1:
 - First public release.
