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.
| Original language | English |
|---|---|
| Journal | Journal of Machine Learning Research |
| Volume | 17 |
| Publication status | Published - 1 Feb 2016 |
| Externally published | Yes |
Keywords
- Classification
- Incremental
- Learning
- Multi-label
- Multi-target
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