Causal MML. Learns Causal Bayesian Networks in Java.
Java Python GLSL Makefile Batchfile Shell
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Camml
example-data
jar
jython
.gitignore
GenericPropertiesCreator.props
LICENSE.txt
README
build.xml
camml.bat
camml.sh
camml_gui.bat
camml_gui.sh

README

Quick guide to getting CaMML started (updated 2015-08-06) :

for the latest src see:
    https://github.com/BayesianIntelligence/CaMML
for docs & discussion see:
    http://groups.google.com/group/camml/
    
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== Installing ==
================

To install camml, simply extract the BI-CaMML.zip file to a folder of your choice.

You will need to make sure you have at least Java 6, and that the "java" program is in your system's PATH variable. (Java will normally do this for you automatically.)

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== Running CaMML with a GUI ==
==============================

== CaMML GUI ==

CaMML has a stand-alone Java-based GUI (added 02/2013) that should be suitable for
most basic learning tasks. The GUI has a data viewer, basic network viewer (based
on Netica libraries), and support for learning DBNs.

- To run the GUI, go to the BI-CaMML directory and use:
  > camml_gui.sh
  > camml_gui.bat (Windows)

At present, this GUI only supports data files that are discrete and contain no
missing values.

== CaMML command line ==

- To get a list of options, go to the BI-CaMML directory and use:
  > camml.sh
  > camml.bat (Windows)

- To train/test a model using weka's default x-fold validation, use:
  > camml.sh Camml/camml/test/iris.arff output.dne
  > camml.bat Camml/camml/test/iris.arff output.dne (Windows)