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      MEKA: A multi-label/multi-target extension to WEKA

      Read, Jesse; Reutemann, Peter; Pfahringer, Bernhard; Holmes, Geoffrey
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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, 17(21), 1–5.
      Permanent Research Commons link: https://hdl.handle.net/10289/10136
      Abstract
      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.
      Date
      2016
      Type
      Journal Article
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      © 2016 Jesse Read, Peter Reutemann, Bernhard Pfahringer, and Geoff Holmes.
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      • Computing and Mathematical Sciences Papers [1455]
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