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

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

All Implemented Interfaces:

BinaryClassifierLearner, ClassifierLearner, java.lang.Cloneable

public class FastRandomTreeLearner
extends RandomTreeLearner

Implements a fast version of the simplest RandomTree learner possible. Avoids memory allocation wheverever possible, with resulting speed up of about 30%

Author:

Alexander Friedman

Nested Class Summary

Nested classes/interfaces inherited from class edu.cmu.minorthird.classify.algorithms.trees.RandomTreeLearner

RandomTreeLearner.BestOfNRandomTreeSplitter, RandomTreeLearner.RandomTreeSplitter, RandomTreeLearner.TreeSplitter

Field Summary

int	subsetSize

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

classifier, dataset

Constructor Summary

FastRandomTreeLearner()

Method Summary

Classifier	batchTrain(Dataset dataset) subclasses should use this method to implement a batch supervised learning algorithm.
Classifier	batchTrain(java.util.List<Example> dataset, java.util.Vector<Feature> allFeatures)
Classifier	batchTrain(java.util.Vector<Example> dataset, int depth, java.util.Vector<Feature> unusedFeatures, int lastFeature, int from, int to)
int	batchTrain(java.util.Vector<Example> dataset, int depth, java.util.Vector<Feature> unusedFeatures, int lastFeature, int from, int to, CompactDecisionTree tree)
FastRandomTreeLearner	setRandomSeed(long seed)
FastRandomTreeLearner	setSubsetSize(int subsetSize)

Methods inherited from class edu.cmu.minorthird.classify.algorithms.trees.RandomTreeLearner

batchTrain

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

Field Detail

subsetSize

public int subsetSize

Constructor Detail

FastRandomTreeLearner

public FastRandomTreeLearner()

Method Detail

setRandomSeed

public FastRandomTreeLearner setRandomSeed(long seed)

setSubsetSize

public FastRandomTreeLearner setSubsetSize(int subsetSize)

batchTrain

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

Overrides:

batchTrain in class RandomTreeLearner

batchTrain

public Classifier batchTrain(Dataset dataset)

Description copied from class: BatchClassifierLearner

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

Overrides:

batchTrain in class RandomTreeLearner

batchTrain

public Classifier batchTrain(java.util.Vector<Example> dataset,
                             int depth,
                             java.util.Vector<Feature> unusedFeatures,
                             int lastFeature,
                             int from,
                             int to)

batchTrain

public int batchTrain(java.util.Vector<Example> dataset,
                      int depth,
                      java.util.Vector<Feature> unusedFeatures,
                      int lastFeature,
                      int from,
                      int to,
                      CompactDecisionTree tree)