edu.cmu.minorthird.classify.algorithms.trees
Class RandomTreeLearner

java.lang.Object
  edu.cmu.minorthird.classify.BatchClassifierLearner
      edu.cmu.minorthird.classify.BatchBinaryClassifierLearner
          edu.cmu.minorthird.classify.algorithms.trees.RandomTreeLearner

All Implemented Interfaces:

BinaryClassifierLearner, ClassifierLearner, java.lang.Cloneable

Direct Known Subclasses:

FastRandomTreeLearner

public class RandomTreeLearner
extends BatchBinaryClassifierLearner

Implement a random decision tree to be used in the random forest learner. Implements two tree splitters. Default one splits on random features. BestOfN splits on the b best of N randomly chosen features.

Author:

Alexander Friedman

Nested Class Summary

static class	RandomTreeLearner.BestOfNRandomTreeSplitter
static class	RandomTreeLearner.RandomTreeSplitter
static interface	RandomTreeLearner.TreeSplitter

Field Summary

Fields inherited from class edu.cmu.minorthird.classify.BatchClassifierLearner

classifier, dataset

Constructor Summary

RandomTreeLearner()

RandomTreeLearner(RandomTreeLearner.TreeSplitter b)

Method Summary

Classifier	batchTrain(Dataset dataset) subclasses should use this method to implement a batch supervised learning algorithm.
edu.cmu.minorthird.classify.algorithms.trees.DecisionTree	batchTrain(java.util.List<Example> dataset, int depth, java.util.Vector<Feature> unusedFeatures)
Classifier	batchTrain(java.util.List<Example> dataset, java.util.Vector<Feature> allFeatures)

Methods inherited from class edu.cmu.minorthird.classify.BatchBinaryClassifierLearner

batchTrainBinary, getBinaryClassifier, getSchema, setSchema

Methods inherited from class edu.cmu.minorthird.classify.BatchClassifierLearner

addExample, completeTraining, copy, getClassifier, hasNextQuery, nextQuery, reset, setInstancePool

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface edu.cmu.minorthird.classify.ClassifierLearner

addExample, completeTraining, copy, getClassifier, hasNextQuery, nextQuery, reset, setInstancePool

Constructor Detail

RandomTreeLearner

public RandomTreeLearner()

RandomTreeLearner

public RandomTreeLearner(RandomTreeLearner.TreeSplitter b)

Method Detail

batchTrain

public Classifier batchTrain(java.util.List<Example> dataset,
                             java.util.Vector<Feature> allFeatures)

batchTrain

public Classifier batchTrain(Dataset dataset)

Description copied from class: BatchClassifierLearner

subclasses should use this method to implement a batch supervised learning algorithm.

Specified by:

batchTrain in class BatchClassifierLearner

batchTrain

public edu.cmu.minorthird.classify.algorithms.trees.DecisionTree batchTrain(java.util.List<Example> dataset,
                                                                            int depth,
                                                                            java.util.Vector<Feature> unusedFeatures)