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MEKA: A multi-label/multi-target extension to WEKA
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Journal of Machine Learning Research, Volume 17, pp. 1-5
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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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Read, J, Reutemann, P, Pfahringer, B & Holmes, G 2016, 'MEKA : A multi-label/multi-target extension to WEKA', Journal of Machine Learning Research, vol. 17, 21, pp. 1-5. < http://www.jmlr.org/papers/volume17/12-164/12-164.pdf >