This page contains the complete material related to "JCHAIDStar: An implementation of the CHAID* algorithm for WEKA".
Below you can find all information related to the most recent update (v1.2, March 2022) done on this implementation.
To access to previous versions:
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Technical information:
Class for generating a decision tree based on the CHAID* algorithm,a modified version of the CHAID decision tree induction algorithm that also handles continuous features and includes the same post-pruning mechanism used by C4.5.
For more information, see:
Igor Ibarguren, Aritz Lasarguren, Jesús M. Pérez, Javier Muguerza, Olatz Arbelaitz and Ibai Gurrutxaga. "BFPART: Best-First PART". Information Sciences (2016). Vol. 367-368. pp. 927-952. doi:10.1016/j.ins.2016.07.023
G. V. Kass. "An Exploratory Technique for Investigating Large Quantities of Categorical Data". Journal of the Royal Statistical Society - Series C (Applied Statistics) (1980), Vol. 29(2), pp 119-127. http://www.jstor.org/stable/2986296
Weka package:
The Weka package containing the JCHAIDStar classifier (tested for weka-3-8-5) to be installed from Weka's package manager, including compiled code, source code, javadocs and package description files, can be found in the official list of Weka packages:
or here:
Source code:
The source code of the classes that implement the JCHAIDStar classifier (on stable-3-8-5 version of Weka) can be found in:
In order to complete the whole source code of the implementation, download the Weka source code from http://www.cs.waikato.ac.nz/ml/weka/downloading.html.
Executable file:
The executable file in Weka is a .jar file. The file with the current JCHAIDStar implementation included in the stable-3-8-5 version of Weka can be found in:
To run Weka type:
java -Xmx1000M -jar Weka-JCHAIDStar.jar
(see http://www.cs.waikato.ac.nz/ml/weka/downloading.html for more information)
Last modification: 2022/03/22