Fix a lot of bugs and generally improve stability, cross-platform functionality standard and unit test coverage. This release has been tested with a large set of unit tests that work across Windows

Also, new features:

• multi-label stratification algorithm and stratification quality measures
• a robust reorganization of label space division, alongside with a working stochastic blockmodel approach and new underlying layer - graph builders that allow using graph models for dividing the label space based not just on label co-occurence but on any kind of network relationships between labels you can come up with
• meka wrapper works fully cross-platform now, including windows 10
• multi-label data set downloading and load/save functionality brought in, like sklearn's dataset
• kNN models support sparse input
• MLARAM models support sparse input
• BSD-compatible label space partitioning via NetworkX
• dependence on GPL libraries made optional
• working predict_proba added for label space partitioning methods
• MLARAM moved to from neurofuzzy to adapt
• test coverage increased to 94%
• Classifier Chains allow specifying the chain order
• lots of documentation updates