Fast Random Forest Algorithm Implementation

Question

I have implemented a small java application using Weka lib with Random Forest. I have trained some classifiers with a sample data and getting a good accuracy of around 85%. However, when i used theFast Random Forest (https://code.google.com/p/fast-random-forest/) it starts throwing error(s).

I have implemented the Fast Random Forest and build it with current jar files. However, it keeps giving the following error when we evaluate the classifier on Training Data:

 "The method evaluateModel(Classifier, Instances, Object...) 
  in the type Evaluation is not applicable for the arguments 
  (FastRandomForest, Instances) "

For this current code:

    FastRandomForest rTree = new FastRandomForest();        
    rTree.buildClassifier(trainingData);

    showTree(rTree);

    System.out.println("records: " + trainingData.attribute(classIndex));
    System.out.println("number of instances: " + trainingData.numInstances());
    System.out.println(trainingData.instance(1));
    System.out.println("target: " + trainingData.classAttribute());
    //System.out.println(rTree.classifyInstance(trainingData.instance(1)));


    /* Evaluate the classifier on Training data */
    Evaluation eTest = new Evaluation(trainingData);
    eTest.evaluateModel(rTree, trainingData); 
    String strSummary = eTest.toSummaryString(); 
    System.out.println(strSummary);

Help appreciated!!

Answer 1

The problem is that FastRandomForest is not assignable to Classifier. You could create an adapter to make the FastRandomForest act like a Classifier.

public class FastRandomForestAdapter : Classifier {
  private FastRandomForest frf;
  public FastRandomForestAdpter(FastRandomForest frf) {
    this.frf = frf;
  }

  @override
  public void MethodA() {
    frf.Method1();
  }

  @override
  public ReturnType MethodB(object arg) {
    return frf.Method2(Transform(arg));
  }

  private Transform(object a) {
    ...
  }
}