Modifier and Type | Field and Description |
---|---|
protected DoubleVector[] |
MultiLabelPrediction.prediction |
Modifier and Type | Field and Description |
---|---|
protected DoubleVector[] |
NaiveBayesMultinomial.m_wordTotalForClass
probability that a word (w) exists in a class (H) (i.e.
|
protected DoubleVector |
NaiveBayes.observedClassDistribution |
Modifier and Type | Method and Description |
---|---|
static double[] |
NaiveBayes.doNaiveBayesPrediction(Instance inst,
DoubleVector observedClassDistribution,
AutoExpandVector<AttributeClassObserver> attributeObservers) |
static double[] |
NaiveBayes.doNaiveBayesPredictionLog(Instance inst,
DoubleVector observedClassDistribution,
AutoExpandVector<AttributeClassObserver> observers,
AutoExpandVector<AttributeClassObserver> observers2) |
Modifier and Type | Field and Description |
---|---|
DoubleVector |
BinaryTreeNumericAttributeClassObserver.Node.classCountsLeft |
DoubleVector |
BinaryTreeNumericAttributeClassObserver.Node.classCountsRight |
DoubleVector |
VFMLNumericAttributeClassObserver.Bin.classWeights |
DoubleVector |
FIMTDDNumericAttributeClassObserver.Node.leftStatistics |
protected DoubleVector |
GaussianNumericAttributeClassObserver.maxValueObservedPerClass |
protected DoubleVector |
GaussianNumericAttributeClassObserver.minValueObservedPerClass |
DoubleVector |
FIMTDDNumericAttributeClassObserver.Node.rightStatistics |
Modifier and Type | Field and Description |
---|---|
AutoExpandVector<DoubleVector> |
NominalAttributeClassObserver.attValDistPerClass |
Modifier and Type | Field and Description |
---|---|
protected DoubleVector |
AdaGrad.m_velocity
Stores the weights (+ bias in the last element)
|
protected DoubleVector[] |
SGDMultiClass.m_weights
Stores the weights (+ bias in the last element)
|
protected DoubleVector |
SGD.m_weights
Stores the weights (+ bias in the last element)
|
protected DoubleVector |
MajorityClass.observedClassDistribution |
Modifier and Type | Method and Description |
---|---|
protected static double |
SGDMultiClass.dotProd(Instance inst1,
DoubleVector weights,
int classIndex) |
protected static double |
SGD.dotProd(Instance inst1,
DoubleVector weights,
int classIndex) |
Modifier and Type | Method and Description |
---|---|
double[] |
ICVarianceReduction.getBranchesSplitMerits(DoubleVector[][] postSplitDists) |
double[] |
ICVarianceReduction.getBranchSplitVarianceOutput(DoubleVector[] postSplitDists) |
double |
ICVarianceReduction.getMeritOfSplit(DoubleVector[] preSplitDist,
DoubleVector[][] postSplitDists) |
double |
ICVarianceReduction.getMeritOfSplit(DoubleVector[] preSplitDist,
DoubleVector[][] postSplitDists) |
protected double |
ICVarianceReduction.getMeritOfSplitForOutput(DoubleVector[] preSplitDist,
DoubleVector[][] postSplitDists,
int outputAttributeIndex) |
protected double |
ICVarianceReduction.getMeritOfSplitForOutput(DoubleVector[] preSplitDist,
DoubleVector[][] postSplitDists,
int outputAttributeIndex) |
protected double |
ICVarianceReduction.getMeritOfSplitForOutput(DoubleVector preSplitDist,
DoubleVector[] postSplitDists) |
protected double |
ICVarianceReduction.getMeritOfSplitForOutput(DoubleVector preSplitDist,
DoubleVector[] postSplitDists) |
double |
ICVarianceReduction.getRangeOfMerit(DoubleVector[] preSplitDist) |
Modifier and Type | Field and Description |
---|---|
DoubleVector |
ISOUPTree.LeafNode.errorM |
DoubleVector |
ISOUPTree.LeafNode.errorP |
protected DoubleVector |
ISOUPTree.InnerNode.PHmins |
protected DoubleVector |
ISOUPTree.InnerNode.PHsums |
protected DoubleVector |
ISOUPTree.InnerNode.sumOfAbsErrors |
protected DoubleVector |
ISOUPTree.Node.sumOfSquares |
protected DoubleVector |
ISOUPTree.Node.sumOfValues |
Modifier and Type | Method and Description |
---|---|
static double |
ISOUPTree.scalarProduct(DoubleVector u,
DoubleVector v) |
Modifier and Type | Field and Description |
---|---|
protected DoubleVector |
RuleClassification.attributeMissingValues |
protected DoubleVector |
RuleClassification.attributesProbability |
protected DoubleVector |
RuleClassification.attributeStatistics |
protected DoubleVector |
RuleClassification.obserClassDistrib |
protected DoubleVector |
RuleClassifier.observedClassDistribution |
protected DoubleVector |
RuleClassifier.ruleClassIndex |
protected DoubleVector |
RuleClassifier.saveBestEntropy |
protected DoubleVector |
RuleClassifier.saveBestEntropyNominalAttrib |
protected DoubleVector |
RuleClassifier.saveBestGlobalEntropy |
protected DoubleVector |
RuleClassification.squaredAttributeStatistics |
Modifier and Type | Method and Description |
---|---|
boolean |
RuleClassifier.checkBestAttrib(double n,
AutoExpandVector<AttributeClassObserver> observerss,
DoubleVector observedClassDistribution) |
double |
RuleClassifier.entropy(DoubleVector ValorDistClassE) |
void |
RuleClassifier.findBestValEntropy(BinaryTreeNumericAttributeClassObserver.Node node,
DoubleVector classCountL,
DoubleVector classCountR,
boolean status,
double minEntropy,
DoubleVector parentCCLeft) |
protected double[] |
RuleClassifier.getBestSecondBestEntropy(DoubleVector entropy) |
protected double[] |
RuleClassifier.oberversDistribProb(Instance inst,
DoubleVector classDistrib) |
Modifier and Type | Method and Description |
---|---|
void |
RuleClassifier.findBestValEntropyNominalAtt(AutoExpandVector<DoubleVector> attrib,
int attNumValues) |
Modifier and Type | Field and Description |
---|---|
protected DoubleVector |
RuleActiveLearningNode.nodeStatistics |
Modifier and Type | Method and Description |
---|---|
static DoubleVector[] |
Utils.copy(DoubleVector[] toCopy) |
static DoubleVector[][] |
Utils.copy(DoubleVector[][] toCopy) |
static DoubleVector |
Utils.floatToDoubleVector(SingleVector toCopy) |
DoubleVector |
RuleActiveLearningNode.getNodeStatistics() |
Modifier and Type | Method and Description |
---|---|
static double |
Utils.computeEntropy(DoubleVector statistics) |
static double |
Utils.computeSD(DoubleVector statistics) |
static double |
Utils.computeVariance(DoubleVector statistics) |
static DoubleVector[] |
Utils.copy(DoubleVector[] toCopy) |
static DoubleVector[][] |
Utils.copy(DoubleVector[][] toCopy) |
static SingleVector[] |
Utils.copyAsFloatVector(DoubleVector[] toCopy) |
Modifier and Type | Field and Description |
---|---|
protected DoubleVector |
MeritFeatureRanking.attributeImportance |
protected DoubleVector |
BasicFeatureRanking.attributeImportance |
Modifier and Type | Method and Description |
---|---|
DoubleVector |
MeritFeatureRanking.getAccumulated() |
DoubleVector |
MeritFeatureRanking.RuleInformation.getAccumulated() |
DoubleVector |
BasicFeatureRanking.RuleInformation.getAccumulatedMerit() |
DoubleVector |
MeritFeatureRanking.RuleInformation.getCurrent() |
DoubleVector |
NoFeatureRanking.getFeatureRankings() |
DoubleVector |
WeightedMajorityFeatureRanking.getFeatureRankings() |
abstract DoubleVector |
AbstractFeatureRanking.getFeatureRankings() |
DoubleVector |
MeritFeatureRanking.getFeatureRankings() |
DoubleVector |
FeatureRanking.getFeatureRankings() |
DoubleVector |
BasicFeatureRanking.getFeatureRankings() |
Modifier and Type | Method and Description |
---|---|
void |
MeritFeatureRanking.RuleInformation.updateCurrent(DoubleVector merits) |
Modifier and Type | Field and Description |
---|---|
protected DoubleVector |
MeritCheckMessage.merits |
Modifier and Type | Method and Description |
---|---|
DoubleVector |
MeritCheckMessage.getMerits() |
Constructor and Description |
---|
MeritCheckMessage(DoubleVector merits) |
MeritCheckMessage(DoubleVector merits,
boolean[] learningAttributes) |
Modifier and Type | Field and Description |
---|---|
DoubleVector |
Perceptron.perceptronattributeStatistics |
DoubleVector |
Perceptron.squaredperceptronattributeStatistics |
Modifier and Type | Field and Description |
---|---|
protected DoubleVector[] |
MultiLabelBSTreeFloat.leftStatistics |
protected DoubleVector[] |
MultiLabelBSTree.leftStatistics |
protected DoubleVector[] |
MultiLabelBSTreeFloat.rightStatistics |
protected DoubleVector[] |
MultiLabelBSTree.rightStatistics |
Modifier and Type | Method and Description |
---|---|
AttributeExpansionSuggestion |
AttributeStatisticsObserver.getBestEvaluatedSplitSuggestion(MultiLabelSplitCriterion criterion,
DoubleVector[] preSplitStatistics,
int inputAttributeIndex)
Gets the best split suggestion given a criterion and a class distribution
|
AttributeExpansionSuggestion |
MultiLabelBSTreeFloat.getBestEvaluatedSplitSuggestion(MultiLabelSplitCriterion criterion,
DoubleVector[] preSplitStatistics,
int inputAttributeIndex) |
AttributeExpansionSuggestion |
MultiLabelNominalAttributeObserver.getBestEvaluatedSplitSuggestion(MultiLabelSplitCriterion criterion,
DoubleVector[] preSplitStatistics,
int inputAttributeIndex) |
AttributeExpansionSuggestion |
MultiLabelBSTree.getBestEvaluatedSplitSuggestion(MultiLabelSplitCriterion criterion,
DoubleVector[] preSplitStatistics,
int inputAttributeIndex) |
void |
AttributeStatisticsObserver.observeAttribute(double inputAttributeValue,
DoubleVector[] statistics)
Updates statistics of this observer given an attribute value, the index of the statistic
and the weight of the instance observed
|
void |
MultiLabelBSTreeFloat.observeAttribute(double inputAttributeValue,
DoubleVector[] statistics) |
void |
MultiLabelBSTreeFloat.Node.observeAttribute(double inputAttributeValue,
DoubleVector[] statistics)
Updates tree with new observation
|
void |
MultiLabelNominalAttributeObserver.observeAttribute(double inputAttributeValue,
DoubleVector[] observedStatistics) |
void |
MultiLabelBSTree.observeAttribute(double inputAttributeValue,
DoubleVector[] statistics) |
void |
MultiLabelBSTree.Node.observeAttribute(double inputAttributeValue,
DoubleVector[] statistics)
Updates tree with new observation
|
protected AttributeExpansionSuggestion |
MultiLabelBSTree.searchForBestSplitOption(MultiLabelBSTree.Node currentNode,
AttributeExpansionSuggestion currentBestOption,
MultiLabelSplitCriterion criterion,
DoubleVector[] preSplitStatistics,
int inputAttributeIndex) |
protected AttributeExpansionSuggestion |
MultiLabelBSTreeFloat.searchForBestSplitOption(MultiLabelBSTreeFloat.Node currentNode,
AttributeExpansionSuggestion currentBestOption,
MultiLabelSplitCriterion criterion,
DoubleVector[] preSplitStatistics,
int inputAttributeIndex) |
Constructor and Description |
---|
Node(double inputAttributeValue,
DoubleVector[] statistics) |
Node(double inputAttributeValue,
DoubleVector[] statistics) |
Modifier and Type | Field and Description |
---|---|
protected DoubleVector[] |
LearningLiteral.literalStatistics |
DoubleVector[][] |
AttributeExpansionSuggestion.resultingNodeStatistics |
Modifier and Type | Method and Description |
---|---|
DoubleVector[][] |
AttributeExpansionSuggestion.getResultingNodeStatistics() |
Constructor and Description |
---|
AttributeExpansionSuggestion(Predicate predicate,
DoubleVector[][] resultingNodeStatistics,
double merit) |
Modifier and Type | Method and Description |
---|---|
double[] |
MultiTargetVarianceRatio.getBranchesSplitMerits(DoubleVector[][] postSplitDists) |
double[] |
MultiLabelSplitCriterion.getBranchesSplitMerits(DoubleVector[][] postSplitDists) |
double[] |
MultilabelInformationGain.getBranchesSplitMerits(DoubleVector[][] postSplitDists) |
double[] |
MultilabelInformationGain.getBranchSplitEntropyOutput(DoubleVector[] postSplitDists) |
double[] |
MultiTargetVarianceRatio.getBranchSplitVarianceOutput(DoubleVector[] postSplitDists) |
double |
MultiTargetVarianceRatio.getMeritOfSplit(DoubleVector[] preSplitDist,
DoubleVector[][] postSplitDists) |
double |
MultiTargetVarianceRatio.getMeritOfSplit(DoubleVector[] preSplitDist,
DoubleVector[][] postSplitDists) |
double |
MultiLabelSplitCriterion.getMeritOfSplit(DoubleVector[] preSplitDist,
DoubleVector[][] postSplitDists) |
double |
MultiLabelSplitCriterion.getMeritOfSplit(DoubleVector[] preSplitDist,
DoubleVector[][] postSplitDists) |
double |
MultilabelInformationGain.getMeritOfSplit(DoubleVector[] preSplitDist,
DoubleVector[][] postSplitDists) |
double |
MultilabelInformationGain.getMeritOfSplit(DoubleVector[] preSplitDist,
DoubleVector[][] postSplitDists) |
protected double |
MultiTargetVarianceRatio.getMeritOfSplitForOutput(DoubleVector[] preSplitDist,
DoubleVector[][] postSplitDists,
int outputAttributeIndex) |
protected double |
MultiTargetVarianceRatio.getMeritOfSplitForOutput(DoubleVector[] preSplitDist,
DoubleVector[][] postSplitDists,
int outputAttributeIndex) |
protected double |
MultilabelInformationGain.getMeritOfSplitForOutput(DoubleVector[] preSplitDist,
DoubleVector[][] postSplitDists,
int outputAttributeIndex) |
protected double |
MultilabelInformationGain.getMeritOfSplitForOutput(DoubleVector[] preSplitDist,
DoubleVector[][] postSplitDists,
int outputAttributeIndex) |
protected double |
MultiTargetVarianceRatio.getMeritOfSplitForOutput(DoubleVector preSplitDist,
DoubleVector[] postSplitDists) |
protected double |
MultiTargetVarianceRatio.getMeritOfSplitForOutput(DoubleVector preSplitDist,
DoubleVector[] postSplitDists) |
protected double |
MultilabelInformationGain.getMeritOfSplitForOutput(DoubleVector preSplitDist,
DoubleVector[] postSplitDists) |
protected double |
MultilabelInformationGain.getMeritOfSplitForOutput(DoubleVector preSplitDist,
DoubleVector[] postSplitDists) |
double |
MultiTargetVarianceRatio.getRangeOfMerit(DoubleVector[] preSplitDist) |
double |
MultiLabelSplitCriterion.getRangeOfMerit(DoubleVector[] preSplitDist) |
double |
MultilabelInformationGain.getRangeOfMerit(DoubleVector[] preSplitDist) |
Modifier and Type | Method and Description |
---|---|
int[] |
VarianceThreshold.getNextOutputIndices(DoubleVector[] resultingStatistics,
DoubleVector[] currentLiteralStatistics,
int[] currentIndices) |
int[] |
VarianceThreshold.getNextOutputIndices(DoubleVector[] resultingStatistics,
DoubleVector[] currentLiteralStatistics,
int[] currentIndices) |
int[] |
EntropyThreshold.getNextOutputIndices(DoubleVector[] resultingStatistics,
DoubleVector[] currentLiteralStatistics,
int[] currentIndices) |
int[] |
EntropyThreshold.getNextOutputIndices(DoubleVector[] resultingStatistics,
DoubleVector[] currentLiteralStatistics,
int[] currentIndices) |
int[] |
OutputAttributesSelector.getNextOutputIndices(DoubleVector[] resultingLiteralStatistics,
DoubleVector[] currentLiteralStatistics,
int[] currentIndices) |
int[] |
OutputAttributesSelector.getNextOutputIndices(DoubleVector[] resultingLiteralStatistics,
DoubleVector[] currentLiteralStatistics,
int[] currentIndices) |
int[] |
StdDevThreshold.getNextOutputIndices(DoubleVector[] resultingStatistics,
DoubleVector[] currentLiteralStatistics,
int[] currentIndices) |
int[] |
StdDevThreshold.getNextOutputIndices(DoubleVector[] resultingStatistics,
DoubleVector[] currentLiteralStatistics,
int[] currentIndices) |
int[] |
SelectAllOutputs.getNextOutputIndices(DoubleVector[] resultingStatistics,
DoubleVector[] currentLiteralStatistics,
int[] currentIndices) |
int[] |
SelectAllOutputs.getNextOutputIndices(DoubleVector[] resultingStatistics,
DoubleVector[] currentLiteralStatistics,
int[] currentIndices) |
Modifier and Type | Field and Description |
---|---|
protected DoubleVector |
DecisionStump.observedClassDistribution |
protected DoubleVector |
HoeffdingOptionTree.Node.observedClassDistribution |
protected DoubleVector |
HoeffdingTree.Node.observedClassDistribution |
protected DoubleVector |
FIMTDD.sumOfAttrSquares |
protected DoubleVector |
FIMTDD.sumOfAttrValues |
protected DoubleVector |
FIMTDD.FIMTDDPerceptron.weightAttribute |
Modifier and Type | Method and Description |
---|---|
DoubleVector |
FIMTDD.FIMTDDPerceptron.getWeights() |
DoubleVector |
FIMTDD.FIMTDDPerceptron.normalizedInstance(Instance inst) |
Modifier and Type | Method and Description |
---|---|
double |
FIMTDD.FIMTDDPerceptron.prediction(DoubleVector instanceValues)
Output the prediction made by this perceptron on the given instance
|
double |
FIMTDD.scalarProduct(DoubleVector u,
DoubleVector v) |
Modifier and Type | Field and Description |
---|---|
protected DoubleVector |
Iadem3.AdaptiveNumericVirtualNode.altClassDist |
protected DoubleVector |
Iadem2.NominalVirtualNode.attValueDist |
protected DoubleVector |
IademGaussianNumericAttributeClassObserver.classDist |
protected DoubleVector |
IademVFMLNumericAttributeClassObserver.classDist |
protected DoubleVector |
Iadem2.Node.classValueDist |
DoubleVector |
IademVFMLNumericAttributeClassObserver.Bin.classWeights |
Modifier and Type | Field and Description |
---|---|
protected AutoExpandVector<DoubleVector> |
Iadem2.NominalVirtualNode.nominalAttClassObserver |
Modifier and Type | Method and Description |
---|---|
abstract DoubleVector |
Iadem2.VirtualNode.computeConditionalProbability(double value) |
DoubleVector |
Iadem2.NominalVirtualNode.computeConditionalProbability(double valor) |
DoubleVector |
Iadem2.NumericVirtualNode.computeConditionalProbability(double value) |
DoubleVector |
Iadem2.Node.getClassValueDist() |
Modifier and Type | Method and Description |
---|---|
AutoExpandVector<DoubleVector> |
Iadem2.NominalVirtualNode.getNominalAttClassObserver() |
Modifier and Type | Method and Description |
---|---|
void |
Iadem2.Node.setClassValueDist(DoubleVector classValueDist) |
Modifier and Type | Method and Description |
---|---|
void |
DoubleVector.addValues(DoubleVector toAdd) |
void |
DoubleVector.subtractValues(DoubleVector toSubtract) |
Constructor and Description |
---|
DoubleVector(DoubleVector toCopy) |
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