The MEKA project provides an open source implementation of methods for multi-label classification and evaluation. It is based on the WEKA Machine Learning Toolkit. Several benchmark methods are also included, as well as the pruned sets and classifier chains methods, other methods from the scientific literature, and a wrapper to the MULAN framework.
The MEKA project provides an open source implementation of methods for multi-label learning and evaluation.
http://waikato.github.io/meka/
See http://waikato.github.io/meka/documentation/ for sources of documentation regarding MEKA.
In particular,
Tutorial.pdf for detailed information on obtaining, using and extending MEKA.If you have a specific question, search the Github issues and, if you can't find a solution, create an issue and label it as question:
https://github.com/Waikato/meka/issues
A list of current Issues in Meka (known bugs, planned improvements, feature wishlist) can be found at https://github.com/Waikato/meka/issues
The Meka developers never have enough time to implement everything that should be in Meka. If you would like to contribute something new to Meka, or help with any of the existing issues, please get in touch with the developers.
FAQs
The MEKA project provides an open source implementation of methods for multi-label classification and evaluation. It is based on the WEKA Machine Learning Toolkit. Several benchmark methods are also included, as well as the pruned sets and classifier chains methods, other methods from the scientific literature, and a wrapper to the MULAN framework.
We found that net.sf.meka:meka demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
In this segment of the Risky Business podcast, Feross Aboukhadijeh and Patrick Gray discuss the challenges of tracking malware discovered in open source softare.
Research
Security News
A threat actor's playbook for exploiting the npm ecosystem was exposed on the dark web, detailing how to build a blockchain-powered botnet.
Security News
NVD’s backlog surpasses 20,000 CVEs as analysis slows and NIST announces new system updates to address ongoing delays.