MEKA: A multi-label/multi-target extension to Weka
Aalto University · Helsinki Institute for Information Technology
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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.
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217
total citations
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Authors
1Topics & keywords
Topics
Keywords
- Computer science
- Java
- Multi-label classification
- Extension (predicate logic)
- Variety (cybernetics)
- Artificial intelligence
- Machine learning
- Open source
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