Quick guide to getting CaMML started (updated 17-02-2013) :

for the latest src see:
    https://github.com/AlexDBlack/CaMML
for docs & discussion see:
    http://groups.google.com/group/camml/
    
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== Installing ==
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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 ==
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== 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 (and Weka Wrapper) ==

CaMML can be used from the command line, by default as a standard weka classifier.
It can also be added to the weka GUI, but that's beyond the scope of this doc.

- 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 -t Camml/camml/test/iris.arff
  > camml.bat -t Camml/camml/test/iris.arff (Windows)