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Decision4j

Decision Trees in Java

decision4j is a decision tree library written in Java.

It's currently at version 0.1, supporting only decision trees for classification. I would like to move this project towards common ensembling methods -- boosting and forests.

Future Enhancements

  • Switch to trove structures
  • Add Jackson support for IO.
  • Support weights on data points better
  • Refactor interfaces

Usage

DecisionTreeModelTest.java shows how to setup and run a decision tree against the iris dataset.

CriterionFactory cf = new CriterionFactory(new CrossEntropy());
ISplitter bs = new BestSplitter(1, cf); // minSamplesInSplit
DecisionTreeFactory dtf = new DecisionTreeFactory();
DecisionTreeLearner dtl = new DecisionTreeLearner(dtf,bs, 4, 100, 100, true); // maxFeatures, maxDepth, maxLeaves, reproposeSplits

//create a new tree model
Model dtm = dtl.create(null);

//train the model        
dtl.trainEpoch(dtm, fvs);

I support common tree building parameters as well as whether to repropose splits for every node.