https://github.com/jd557/weka-emiodc
Weka Package containing multiple ordinal data classifiers
https://github.com/jd557/weka-emiodc
Last synced: 11 months ago
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Weka Package containing multiple ordinal data classifiers
- Host: GitHub
- URL: https://github.com/jd557/weka-emiodc
- Owner: JD557
- Created: 2016-02-20T18:06:32.000Z (over 10 years ago)
- Default Branch: master
- Last Pushed: 2016-03-21T19:57:11.000Z (over 10 years ago)
- Last Synced: 2025-08-31T23:58:41.656Z (11 months ago)
- Language: Java
- Size: 58.6 KB
- Stars: 6
- Watchers: 4
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
Ensemble Methods in Ordinal Classification
==========================================
This repository contains the implementation of the various algorithms presented
in [Ensemble Methods in Ordinal Data Classification](https://repositorio-aberto.up.pt/handle/10216/73795?locale=en)
for Weka 3.7.
Included Algorithms
-------------------
* oAdaBoost: [oAdaBoost: An AdaBoost variant for Ordinal Data Classification](http://joaocosta.eu/Portfolio/docs/pubs/oAdaboost2015.pdf)
* AdaBoost.OR: [Combining ordinal preferences by boosting](https://www.csie.ntu.edu.tw/~htlin/paper/doc/wspl09adaboostor.pdf)
* AdaBoost.M1w: [How to make AdaBoost.M1 work for weak base classifiers by changing only one line of the code](http://www.en-trust.at/eibl/wp-content/uploads/sites/3/2013/08/Eibl02_ECML_AdaBoostM1W.pdf)
* oDT: [Ensemble Methods in Ordinal Data Classification](https://repositorio-aberto.up.pt/bitstream/10216/73795/2/99372.pdf)
* Ordinal Random Forests: [Ensemble Methods in Ordinal Data Classification](https://repositorio-aberto.up.pt/bitstream/10216/73795/2/99372.pdf)
Instalation
-----------
### Download (Recommended)
1. Download the pre-compiled package from https://github.com/JD557/weka-emiodc/releases
2. Open Weka 3.7 and choose `Tools > Package Manager`
3. Click on `File/URL` (under `Unofficial`) and choose the downloaded .zip
4. Restart Weka
5. You should now an `OrdinalEnsembleMethods` package
6. The new classifiers should now be available
### Compile from source
1. Run `sbt package`
2. Compress the compiled jar (`target/scala-2.10/emiodc_2.10-1.0.jar`) alongside the `Description.props` in a zip
2. Open Weka 3.7 and choose `Tools > Package Manager`
3. Click on `File/URL` (under `Unofficial`) and choose the generated .zip
4. Restart Weka
5. You should now an `OrdinalEnsembleMethods` package
6. The new classifiers should now be available