We have developed and are constantly enriching a Java library for Multi-label learning, called Mulan. Mulan contains several problem transformation and algorithm adaptation methods for multilabel classification and ranking, an evaluation framework that computes several multilabel classification evaluation measures and a class providing data set statistics. It also contains an algorithm and support for hierarchical multi-label classification. Mulan is built on top of Weka and it therefore utilizes its award-wining code base. It is open-source and distributed under the GNU GPL licence. Please contact Grigorios Tsoumakas for bug reports, comments, suggestions or request for help with the library. ·
http://mlkd.csd.auth.gr/multilabel.htmlWe have developed and are constantly enriching a Java library for Multi-label learning, called Mulan. Mulan contains several problem transformation and algorithm adaptation methods for multilabel classification and ranking, an evaluation framework that computes several multilabel classification evaluation measures and a class providing data set statistics. It also contains an algorithm and support for hierarchical multi-label classification. Mulan is built on top of Weka and it therefore utilizes its award-wining code base. It is open-source and distributed under the GNU GPL licence. Please contact Grigorios Tsoumakas for bug reports, comments, suggestions or request for help with the library. ·
http://mlkd.csd.auth.gr/multilabel.html