MEKA: A Multi-label/Multi-Target Extension to WEKA
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.
Cite
Text
Read et al. "MEKA: A Multi-label/Multi-Target Extension to WEKA." Machine Learning Open Source Software, 2016.Markdown
[Read et al. "MEKA: A Multi-label/Multi-Target Extension to WEKA." Machine Learning Open Source Software, 2016.](https://mlanthology.org/mloss/2016/read2016jmlr-meka/)BibTeX
@article{read2016jmlr-meka,
title = {{MEKA: A Multi-label/Multi-Target Extension to WEKA}},
author = {Read, Jesse and Reutemann, Peter and Pfahringer, Bernhard and Holmes, Geoff},
journal = {Machine Learning Open Source Software},
year = {2016},
pages = {1-5},
volume = {17},
url = {https://mlanthology.org/mloss/2016/read2016jmlr-meka/}
}