This is a simple implementation of the decision tree algorithm from Ross Quinlan for Scala 

The reason for this little project is that all other implementations and libraries of the id3/c 4.5 algorithms I have worked with, have the limitation that it is not possible to access the generated tree structure. Also none of them are able to operate on a domain model instead of tabular data. So far this little prototype solves at least these 2 problems.

If you want to build the project, make sure sbt is installed, then execute the commands:  
git clone git://github.com/mkleen/baum.git
cd baum
sbt update
sbt compile
 
Have a look at src/test/scala/baum/WeatherExample1.scala which models a classical example from the book "Datamining - Practical Machine Learning Tools and Techniques" from  I. Witten and Eibe Frank. You can run the example with the  following command:
sbt test-only baum.WeatherExample1

There are a couple of features missing, most of them are part of the c 4.5 version of the algorithm: 
- Integrate confidence score 
- Support for numerical values
- Support for missing values 
- Tree pruning