ai.libs.jaicore.ml.intervaltree

Class ExtendedRandomForest

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.SingleClassifierEnhancer

weka.classifiers.IteratedSingleClassifierEnhancer

weka.classifiers.ParallelIteratedSingleClassifierEnhancer

weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer

weka.classifiers.meta.Bagging

weka.classifiers.trees.RandomForest

ai.libs.jaicore.ml.intervaltree.ExtendedRandomForest

All Implemented Interfaces:

RangeQueryPredictor, java.io.Serializable, java.lang.Cloneable, weka.classifiers.Classifier, weka.core.AdditionalMeasureProducer, weka.core.Aggregateable<weka.classifiers.meta.Bagging>, weka.core.BatchPredictor, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, weka.core.OptionHandler, weka.core.PartitionGenerator, weka.core.Randomizable, weka.core.RevisionHandler, weka.core.TechnicalInformationHandler, weka.core.WeightedInstancesHandler

public class ExtendedRandomForest
extends weka.classifiers.trees.RandomForest
implements RangeQueryPredictor

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.classifiers.trees.RandomForest

m_computeAttributeImportance

Fields inherited from class weka.classifiers.meta.Bagging

m_BagSizePercent, m_CalcOutOfBag, m_classifiersCache, m_data, m_inBag, m_OutOfBagEvaluationObject, m_random, m_RepresentUsingWeights

Fields inherited from class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer

m_Seed

Fields inherited from class weka.classifiers.ParallelIteratedSingleClassifierEnhancer

m_numExecutionSlots

Fields inherited from class weka.classifiers.IteratedSingleClassifierEnhancer

m_Classifiers, m_NumIterations

Fields inherited from class weka.classifiers.SingleClassifierEnhancer

m_Classifier

Fields inherited from class weka.classifiers.AbstractClassifier

BATCH_SIZE_DEFAULT, m_BatchSize, m_Debug, m_DoNotCheckCapabilities, m_numDecimalPlaces, NUM_DECIMAL_PLACES_DEFAULT

Constructor Summary

Constructors

Constructor and Description
ExtendedRandomForest()
ExtendedRandomForest(FeatureSpace featureSpace)
ExtendedRandomForest(int seed)
ExtendedRandomForest(IntervalAggregator treeAggregator, IntervalAggregator forestAggregator)
ExtendedRandomForest(IntervalAggregator treeAggregator, IntervalAggregator forestAggregator, FeatureSpace featureSpace)

Method Summary

Modifier and Type	Method and Description
double	computeMarginalVarianceContributionForFeatureSubset(java.util.Set<java.lang.Integer> features)
double	computeMarginalVarianceContributionForFeatureSubsetNotNormalized(java.util.Set<java.lang.Integer> features)
protected java.lang.String	defaultClassifierString()
FeatureSpace	getFeatureSpace()
int	getSize()
org.apache.commons.math3.geometry.euclidean.oned.Interval	predictInterval(weka.core.Instance rangeQuery)
org.apache.commons.math3.geometry.euclidean.oned.Interval	predictInterval(RQPHelper.IntervalAndHeader intervalAndHeader)
void	prepareForest(weka.core.Instances data) Needs to be called before predicting marginal variance contributions!
void	printVariances()

Methods inherited from class weka.classifiers.trees.RandomForest

breakTiesRandomlyTipText, computeAttributeImportanceTipText, computeAverageImpurityDecreasePerAttribute, defaultClassifierOptions, defaultNumberOfIterations, getBreakTiesRandomly, getCapabilities, getComputeAttributeImportance, getMaxDepth, getNumFeatures, getOptions, getRevision, getTechnicalInformation, globalInfo, listOptions, main, maxDepthTipText, numFeaturesTipText, setBatchSize, setBreakTiesRandomly, setClassifier, setComputeAttributeImportance, setDebug, setMaxDepth, setNumDecimalPlaces, setNumFeatures, setOptions, setRepresentCopiesUsingWeights, setSeed, toString

Methods inherited from class weka.classifiers.meta.Bagging

aggregate, bagSizePercentTipText, buildClassifier, calcOutOfBagTipText, distributionForInstance, enumerateMeasures, finalizeAggregation, generatePartition, getBagSizePercent, getCalcOutOfBag, getMeasure, getMembershipValues, getOutOfBagEvaluationObject, getOutputOutOfBagComplexityStatistics, getPrintClassifiers, getRepresentCopiesUsingWeights, getStoreOutOfBagPredictions, getTrainingSet, measureOutOfBagError, numElements, outputOutOfBagComplexityStatisticsTipText, printClassifiersTipText, representCopiesUsingWeightsTipText, setBagSizePercent, setCalcOutOfBag, setOutputOutOfBagComplexityStatistics, setPrintClassifiers, setStoreOutOfBagPredictions, storeOutOfBagPredictionsTipText

Methods inherited from class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer

getSeed, seedTipText

Methods inherited from class weka.classifiers.ParallelIteratedSingleClassifierEnhancer

buildClassifiers, getNumExecutionSlots, numExecutionSlotsTipText, setNumExecutionSlots

Methods inherited from class weka.classifiers.IteratedSingleClassifierEnhancer

getNumIterations, numIterationsTipText, setNumIterations

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

classifierTipText, getClassifier, getClassifierSpec, postExecution, preExecution

Methods inherited from class weka.classifiers.AbstractClassifier

batchSizeTipText, classifyInstance, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setDoNotCheckCapabilities

Methods inherited from class java.lang.Object

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

Constructor Detail

ExtendedRandomForest

public ExtendedRandomForest()

ExtendedRandomForest

public ExtendedRandomForest(IntervalAggregator treeAggregator,
                            IntervalAggregator forestAggregator)

ExtendedRandomForest

public ExtendedRandomForest(FeatureSpace featureSpace)

ExtendedRandomForest

public ExtendedRandomForest(IntervalAggregator treeAggregator,
                            IntervalAggregator forestAggregator,
                            FeatureSpace featureSpace)

ExtendedRandomForest

public ExtendedRandomForest(int seed)

Method Detail

prepareForest

public void prepareForest(weka.core.Instances data)

Needs to be called before predicting marginal variance contributions!

Parameters:

Instances - for which marginal variance contributions are to be estimated

printVariances

public void printVariances()

computeMarginalVarianceContributionForFeatureSubset

public double computeMarginalVarianceContributionForFeatureSubset(java.util.Set<java.lang.Integer> features)

computeMarginalVarianceContributionForFeatureSubsetNotNormalized

public double computeMarginalVarianceContributionForFeatureSubsetNotNormalized(java.util.Set<java.lang.Integer> features)

getSize

public int getSize()

Returns:

Size of

getFeatureSpace

public FeatureSpace getFeatureSpace()

Returns:

Feature space on which this forest operates on

defaultClassifierString

protected java.lang.String defaultClassifierString()

Overrides:

defaultClassifierString in class weka.classifiers.trees.RandomForest

predictInterval

public org.apache.commons.math3.geometry.euclidean.oned.Interval predictInterval(weka.core.Instance rangeQuery)

Specified by:

predictInterval in interface RangeQueryPredictor

predictInterval

public org.apache.commons.math3.geometry.euclidean.oned.Interval predictInterval(RQPHelper.IntervalAndHeader intervalAndHeader)

Specified by:

predictInterval in interface RangeQueryPredictor