https://github.com/fracpete/mlrules-weka-package

Weka package for Maximum Likelihood Rule Ensembles (MLRules)
https://github.com/fracpete/mlrules-weka-package

weka weka-package

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Weka package for Maximum Likelihood Rule Ensembles (MLRules)

• Host: GitHub
• URL: https://github.com/fracpete/mlrules-weka-package
• Owner: fracpete
• License: gpl-3.0
• Created: 2023-07-25T21:43:16.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-07-25T22:52:38.000Z (about 1 year ago)
• Last Synced: 2023-07-25T23:34:59.320Z (about 1 year ago)
• Topics: weka, weka-package
• Language: Java
• Homepage:
• Size: 6.77 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# mlrules-weka-package

Maximum Likelihood Rule Ensembles (MLRules) is a new rule induction algorithm for 

solving classification problems via probability estimation. The ensemble is built 

using boosting, by greedily minimizing the negative loglikelihood which results 

in estimating the class conditional probability distribution. The main advantage 

of decision rules is their simplicity and comprehensibility: they are logical 

statements of the form "if condition then decision", which is probably the easiest 

form of model to interpret. On the other hand, by exploiting a powerful statistical 

technique to induce the rules, the final ensemble has very high prediction accuracy. 

Fork of the original code located here:

http://www.cs.put.poznan.pl/wkotlowski/software-mlrules.html

## Citation

```

@article{DemKotSlo08MLRules,

  author    = {Krzysztof Dembczy\'nski and Wojciech Kot{\l}owski and Roman S{\l}owi\'nski},  

  title     = {Maximum likelihood rule ensembles},

  booktitle = {Proceedings of the 25th International Conference on Machine Learning (ICML 2008)},

  year      = {2008}

}

```

## Changes

* Turned into a Weka package

* Uses a seeded random number generator now (superclass: `weka.classifiers.RandomizableClassifier`)

## Releases

* [2023.7.26](https://github.com/fracpete/mlrules-weka-package/releases/download/v2023.7.26/mlrules-2023.7.26.zip)

## Maven

Use the following dependency in your `pom.xml`:

```xml

    

      com.github.fracpete

      mlrules-weka-package

      2023.7.26

      jar

      

        

          nz.ac.waikato.cms.weka

          weka-dev

        

      

    

```

## How to use packages

For more information on how to install the package, see:

https://waikato.github.io/weka-wiki/packages/manager/