About: A native Python, scikit-compatible, implementation of a variety of multi-label classification algorithms.

• a general matrix-based label space clusterer has been added which can cluster the output space using any scikit-learn compatible clusterer (incl. k-means)
• support for more single-class and multi-class classifiers you can now use problem transformation approaches with your favourite neural networks/deep learning libraries: theano, tensorflow, keras, scikit-neuralnetworks
• support for label powerset based stratified kfold added
• graph-tool clusterer supports weighted graphs again and includes stochastic blockmodel calibration
• bugs were fixed in: classifier chains and hierarchical neuro fuzzy clasifiers