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Class implementing decision forest algorithm Forest PA, using bootstrap samples and penalized attributes. Uses and depends on SimpleCart.

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ForestPA

Class implementing decision forest algorithm Forest PA, using bootstrap samples and penalized attributes. Uses and depends on SimpleCart.

For more information, see:

Adnan, Md Nasim, Md Zahidul Islam (2017). Forest PA: Constructing a Decision Forest by Penalizing Attributes used in Previous Trees. Expert Systems with Applications.

BibTeX:

\article{adnan2017forest,
  title={Forest PA: Constructing a Decision Forest by Penalizing Attributes used in Previous Trees},
  author={Adnan, Md Nasim and Islam, Md Zahidul},
  journal={Expert Systems with Applications},
  year={2017},
  publisher={Elsevier}
}

Installation

Either download ForestPA from the Weka package manager, or download the latest release from the "Releases" section on the sidebar of Github. A video of how to install and use the package can be found here

Compilation / Development

Set up a project in your IDE of choice, including weka.jar and simpleCART.jar as compile-time libraries. simpleCART.jar is available in the Weka package manager.

Valid options are:

-T <num trees> Number of trees requested in the forest. (default 10)

-M <min no> The minimal number of instances at the terminal nodes of each SimpleCart. (default 2)

-N <num folds> The number of folds used in the minimal cost-complexity pruning for each SimpleCart. (default 5)

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Class implementing decision forest algorithm Forest PA, using bootstrap samples and penalized attributes. Uses and depends on SimpleCart.

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