public class FIMTDD extends AbstractClassifier implements Regressor
Modifier and Type | Class and Description |
---|---|
class |
FIMTDD.FIMTDDPerceptron |
static class |
FIMTDD.InnerNode |
static class |
FIMTDD.LeafNode |
static class |
FIMTDD.Node |
static class |
FIMTDD.SplitNode |
Modifier and Type | Field and Description |
---|---|
FloatOption |
alternateTreeFadingFactorOption |
IntOption |
alternateTreeTimeOption |
IntOption |
alternateTreeTMinOption |
protected double |
examplesSeen |
IntOption |
gracePeriodOption |
protected int |
leafNodeCount |
FloatOption |
learningRateDecayFactorOption |
FlagOption |
learningRatioConstOption |
FloatOption |
learningRatioOption |
int |
maxID |
FloatOption |
PageHinckleyAlphaOption |
IntOption |
PageHinckleyThresholdOption |
FlagOption |
regressionTreeOption |
FloatOption |
splitConfidenceOption |
ClassOption |
splitCriterionOption |
protected int |
splitNodeCount |
protected DoubleVector |
sumOfAttrSquares |
protected DoubleVector |
sumOfAttrValues |
protected double |
sumOfSquares |
protected double |
sumOfValues |
FloatOption |
tieThresholdOption |
protected FIMTDD.Node |
treeRoot |
classifierRandom, modelContext, randomSeed, randomSeedOption, trainingWeightSeenByModel
config
Constructor and Description |
---|
FIMTDD() |
Modifier and Type | Method and Description |
---|---|
protected void |
attemptToSplit(FIMTDD.LeafNode node,
FIMTDD.Node parent,
int parentIndex) |
boolean |
buildingModelTree() |
int |
calcByteSize() |
protected void |
checkRoot() |
static double |
computeHoeffdingBound(double range,
double confidence,
double n) |
double |
computeSD(double squaredVal,
double val,
double size) |
void |
getModelDescription(StringBuilder out,
int indent)
Returns a string representation of the model.
|
protected Measurement[] |
getModelMeasurementsImpl()
Gets the current measurements of this classifier.
The reason for ...Impl methods: ease programmer burden by not requiring them to remember calls to super in overridden methods. |
double |
getNormalizedError(Instance inst,
double prediction) |
String |
getPurposeString()
Dictionary with option texts and objects
|
double[] |
getVotesForInstance(Instance inst)
Predicts the class memberships for a given instance.
|
boolean |
isRandomizable()
Gets whether this learner needs a random seed.
|
protected FIMTDD.FIMTDDPerceptron |
newLeafModel() |
protected FIMTDD.LeafNode |
newLeafNode() |
protected FIMTDDNumericAttributeClassObserver |
newNumericClassObserver() |
protected FIMTDD.SplitNode |
newSplitNode(InstanceConditionalTest splitTest) |
double |
normalizeTargetValue(double value) |
void |
processInstance(Instance inst,
FIMTDD.Node node,
double prediction,
double normalError,
boolean growthAllowed,
boolean inAlternate) |
void |
resetLearningImpl()
Resets this classifier.
|
double |
scalarProduct(DoubleVector u,
DoubleVector v) |
void |
trainOnInstanceImpl(Instance inst)
Method for updating (training) the model using a new instance
|
contextIsCompatible, copy, correctlyClassifies, getAttributeNameString, getAWTRenderer, getClassLabelString, getClassNameString, getDescription, getModel, getModelContext, getModelMeasurements, getNominalValueString, getPredictionForInstance, getPredictionForInstance, getSubClassifiers, getSublearners, getVotesForInstance, modelAttIndexToInstanceAttIndex, modelAttIndexToInstanceAttIndex, prepareForUseImpl, resetLearning, setModelContext, setRandomSeed, trainingHasStarted, trainingWeightSeenByModel, trainOnInstance, trainOnInstance
getCLICreationString, getOptions, getPreparedClassOption, prepareClassOptions, prepareForUse, prepareForUse
copy, measureByteSize, measureByteSize, toString
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
getCLICreationString, getOptions, prepareForUse, prepareForUse
measureByteSize
protected FIMTDD.Node treeRoot
protected int leafNodeCount
protected int splitNodeCount
protected double examplesSeen
protected double sumOfValues
protected double sumOfSquares
protected DoubleVector sumOfAttrValues
protected DoubleVector sumOfAttrSquares
public int maxID
public ClassOption splitCriterionOption
public IntOption gracePeriodOption
public FloatOption splitConfidenceOption
public FloatOption tieThresholdOption
public FloatOption PageHinckleyAlphaOption
public IntOption PageHinckleyThresholdOption
public FloatOption alternateTreeFadingFactorOption
public IntOption alternateTreeTMinOption
public IntOption alternateTreeTimeOption
public FlagOption regressionTreeOption
public FloatOption learningRatioOption
public FloatOption learningRateDecayFactorOption
public FlagOption learningRatioConstOption
public String getPurposeString()
AbstractOptionHandler
getPurposeString
in interface OptionHandler
getPurposeString
in class AbstractClassifier
public void resetLearningImpl()
AbstractClassifier
resetLearningImpl
in class AbstractClassifier
public boolean isRandomizable()
Learner
isRandomizable
in interface Learner<Example<Instance>>
public void getModelDescription(StringBuilder out, int indent)
AbstractClassifier
getModelDescription
in class AbstractClassifier
out
- the stringbuilder to add the descriptionindent
- the number of characters to indentprotected Measurement[] getModelMeasurementsImpl()
AbstractClassifier
getModelMeasurementsImpl
in class AbstractClassifier
public int calcByteSize()
public double[] getVotesForInstance(Instance inst)
Classifier
getVotesForInstance
in interface Classifier
getVotesForInstance
in class AbstractClassifier
inst
- the instance to be classifiedpublic double normalizeTargetValue(double value)
public double getNormalizedError(Instance inst, double prediction)
public void trainOnInstanceImpl(Instance inst)
trainOnInstanceImpl
in class AbstractClassifier
inst
- the instance to be used for trainingpublic void processInstance(Instance inst, FIMTDD.Node node, double prediction, double normalError, boolean growthAllowed, boolean inAlternate)
protected FIMTDDNumericAttributeClassObserver newNumericClassObserver()
protected FIMTDD.SplitNode newSplitNode(InstanceConditionalTest splitTest)
protected FIMTDD.LeafNode newLeafNode()
protected FIMTDD.FIMTDDPerceptron newLeafModel()
protected void checkRoot()
public static double computeHoeffdingBound(double range, double confidence, double n)
public boolean buildingModelTree()
protected void attemptToSplit(FIMTDD.LeafNode node, FIMTDD.Node parent, int parentIndex)
public double computeSD(double squaredVal, double val, double size)
public double scalarProduct(DoubleVector u, DoubleVector v)
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