MEKA: A multi-label/multi-target extension to WEKA. Multi-label classification has rapidly attracted interest in the machine learning literature, and there are now a large number and considerable variety of methods for this type of learning. We present MEKA: an open-source Java framework based on the well-known WEKA library. MEKA provides interfaces to facilitate practical application, and a wealth of multi-label classifiers, evaluation metrics, and tools for multi-label experiments and development. It supports multi-label and multi-target data, including in incremental and semi-supervised contexts.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Piotr Szymanski: A scikit-based Python environment for performing multi-label classification (2017) arXiv
- Read, Jesse; Reutemann, Peter; Pfahringer, Bernhard; Holmes, Geoff: MEKA: a multi-label/multi-target extension to WEKA (2016)