Uses of Class
org.jpmml.evaluator.Value

Packages that use Value

Package	Description
org.jpmml.evaluator
org.jpmml.evaluator.clustering
org.jpmml.evaluator.general_regression
org.jpmml.evaluator.mining
org.jpmml.evaluator.neural_network
org.jpmml.evaluator.regression
org.jpmml.evaluator.scorecard
org.jpmml.evaluator.support_vector_machine

Uses of Value in org.jpmml.evaluator

Subclasses of Value in org.jpmml.evaluator

Modifier and Type	Class	Description
class	DoubleValue
class	FloatValue

Methods in org.jpmml.evaluator that return Value

Modifier and Type	Method	Description
abstract Value<V>	Value.abs()
abstract Value<V>	Value.add(java.lang.Number value)
abstract Value<V>	Value.add(java.lang.Number coefficient, java.lang.Number factor)	Adds coefficient * factor.
abstract Value<V>	Value.add(java.lang.Number coefficient, java.lang.Number... factors)	Adds coefficient * product(factors).
abstract Value<V>	Value.add(java.lang.Number coefficient, java.lang.Number factor, int exponent)	Adds coefficient * (factor ^ exponent).
abstract Value<V>	Value.add(java.lang.Number coefficient, java.lang.Number firstFactor, java.lang.Number secondFactor)
abstract Value<V>	Value.add(Value<? extends java.lang.Number> value)
abstract Value<V>	Value.arctan()
Value<V>	ValueAggregator.average()
static <V extends java.lang.Number> Value<V>	MeasureUtil.calculateAdjustment(ValueFactory<V> valueFactory, java.util.List<FieldValue> values)
static <V extends java.lang.Number> Value<V>	MeasureUtil.calculateAdjustment(ValueFactory<V> valueFactory, java.util.List<FieldValue> values, java.util.List<? extends java.lang.Number> adjustmentValues)
abstract Value<V>	Value.ceiling()
abstract Value<V>	Value.copy()
abstract Value<V>	Value.cos()
static <V extends java.lang.Number> Value<V>	NormalizationUtil.denormalize(org.dmg.pmml.NormContinuous normContinuous, Value<V> value)
abstract Value<V>	Value.denormalize(java.lang.Number leftOrig, java.lang.Number leftNorm, java.lang.Number rightOrig, java.lang.Number rightNorm)
abstract Value<V>	Value.divide(java.lang.Number value)
abstract Value<V>	Value.divide(Value<? extends java.lang.Number> value)
abstract Value<V>	Value.elliott()
protected Value<V>	ValueMap.ensureValue(K key)
static <V extends java.lang.Number> Value<V>	MeasureUtil.evaluateDistance(ValueFactory<V> valueFactory, org.dmg.pmml.ComparisonMeasure comparisonMeasure, java.util.List<? extends org.dmg.pmml.ComparisonField<?>> comparisonFields, java.util.List<FieldValue> values, java.util.List<FieldValue> referenceValues, Value<V> adjustment)
static <V extends java.lang.Number> Value<V>	TargetUtil.evaluateRegressionInternal(TargetField targetField, Value<V> value)
static <V extends java.lang.Number> Value<V>	MeasureUtil.evaluateSimilarity(ValueFactory<V> valueFactory, org.dmg.pmml.ComparisonMeasure comparisonMeasure, java.util.List<? extends org.dmg.pmml.ComparisonField<?>> comparisonFields, java.util.BitSet flags, java.util.BitSet referenceFlags)
abstract Value<V>	Value.exp()
abstract Value<V>	Value.floor()
abstract Value<V>	Value.gauss()
abstract Value<V>	Value.gaussSim(java.lang.Number value)
Value<java.lang.Double>	DoubleVector.get(int index)
Value<java.lang.Float>	FloatVector.get(int index)
abstract Value<V>	Vector.get(int index)
Value<V>	Regression.getValue()
abstract Value<V>	Value.inverseCauchit()
abstract Value<V>	Value.inverseCloglog()
abstract Value<V>	Value.inverseLogc()
abstract Value<V>	Value.inverseLogit()
abstract Value<V>	Value.inverseLoglog()
abstract Value<V>	Value.inverseNegbin(java.lang.Number value)
abstract Value<V>	Value.inverseOddspower(java.lang.Number value)
abstract Value<V>	Value.inversePower(java.lang.Number value)
abstract Value<V>	Value.inverseProbit()
abstract Value<V>	Value.ln()
Value<java.lang.Double>	DoubleVector.max()
Value<java.lang.Float>	FloatVector.max()
abstract Value<V>	Vector.max()
Value<java.lang.Double>	DoubleVector.median()
Value<java.lang.Float>	FloatVector.median()
Value<V>	ValueAggregator.median()
abstract Value<V>	Vector.median()
abstract Value<V>	Value.multiply(java.lang.Number value)
abstract Value<V>	Value.multiply(java.lang.Number factor, java.lang.Number exponent)	Multiplies by factor ^ exponent.
abstract Value<V>	Value.multiply(Value<? extends java.lang.Number> value)
abstract Value<V>	ValueFactory.newValue()	Creates a value, which is "silently" set to the zero value.
abstract Value<V>	ValueFactory.newValue(java.lang.Number value)	Creates a value, which is "vocally" set to the specified value.
abstract Value<V>	ValueFactory.newValue(java.lang.String value)	Creates a value, which is "vocally" set to the specified value.
Value<java.lang.Double>	ValueFactoryFactory.DoubleValueFactory.newValue()
Value<java.lang.Double>	ValueFactoryFactory.DoubleValueFactory.newValue(java.lang.Number value)
Value<java.lang.Double>	ValueFactoryFactory.DoubleValueFactory.newValue(java.lang.String value)
Value<java.lang.Float>	ValueFactoryFactory.FloatValueFactory.newValue()
Value<java.lang.Float>	ValueFactoryFactory.FloatValueFactory.newValue(java.lang.Number value)
Value<java.lang.Float>	ValueFactoryFactory.FloatValueFactory.newValue(java.lang.String value)
static <V extends java.lang.Number> Value<V>	NormalizationUtil.normalize(org.dmg.pmml.NormContinuous normContinuous, Value<V> value)
abstract Value<V>	Value.normalize(java.lang.Number leftOrig, java.lang.Number leftNorm, java.lang.Number rightOrig, java.lang.Number rightNorm)
abstract Value<V>	Value.power(java.lang.Number value)
static <V extends java.lang.Number> Value<V>	TargetUtil.processValue(org.dmg.pmml.Target target, Value<V> value)
abstract Value<V>	Value.reciprocal()
abstract Value<V>	Value.relu()
abstract Value<V>	Value.reset(java.lang.Number value)
abstract Value<V>	Value.residual(Value<? extends java.lang.Number> value)
abstract Value<V>	Value.restrict(java.lang.Number lowValue, java.lang.Number highValue)
abstract Value<V>	Value.round()
abstract Value<V>	Value.sin()
abstract Value<V>	Value.square()
abstract Value<V>	Value.subtract(java.lang.Number value)
abstract Value<V>	Value.subtract(Value<? extends java.lang.Number> value)
Value<java.lang.Double>	DoubleVector.sum()
Value<java.lang.Float>	FloatVector.sum()
Value<V>	ValueAggregator.sum()
static <V extends java.lang.Number> Value<V>	ValueUtil.sum(java.lang.Iterable<Value<V>> values)
abstract Value<V>	Vector.sum()
abstract Value<V>	Value.tanh()
abstract Value<V>	Value.threshold(java.lang.Number value)
Value<V>	ValueAggregator.weightedAverage()
Value<V>	ValueAggregator.weightedMedian()
Value<V>	ValueAggregator.weightedSum()

Methods in org.jpmml.evaluator that return types with arguments of type Value

Modifier and Type	Method	Description
protected java.util.Map<K,Value<V>>	KeyValueAggregator.asTransformedMap(com.google.common.base.Function<Vector<V>,Value<V>> function)
protected static <K,V extends java.lang.Number> com.google.common.collect.Ordering<java.util.Map.Entry<K,Value<V>>>	Classification.createOrdering(Classification.Type type)
protected java.util.Set<java.util.Map.Entry<K,Value<V>>>	Classification.entrySet()
protected java.util.Map.Entry<K,Value<V>>	Classification.getWinner()
static <K,V extends java.lang.Number> java.util.Map.Entry<K,Value<V>>	Classification.getWinner(Classification.Type type, java.util.Collection<java.util.Map.Entry<K,Value<V>>> entries)
static <K,V extends java.lang.Number> java.util.List<java.util.Map.Entry<K,Value<V>>>	Classification.getWinnerList(Classification.Type type, java.util.Collection<java.util.Map.Entry<K,Value<V>>> entries)
protected java.util.List<java.util.Map.Entry<K,Value<V>>>	Classification.getWinnerRanking()
java.util.Iterator<Value<V>>	ValueMap.iterator()

Methods in org.jpmml.evaluator with parameters of type Value

Modifier and Type	Method	Description
DoubleVector	ComplexDoubleVector.add(Value<? extends java.lang.Number> value)
FloatVector	ComplexFloatVector.add(Value<? extends java.lang.Number> value)
DoubleValue	DoubleValue.add(Value<? extends java.lang.Number> value)
FloatValue	FloatValue.add(Value<? extends java.lang.Number> value)
DoubleVector	SimpleDoubleVector.add(Value<? extends java.lang.Number> value)
FloatVector	SimpleFloatVector.add(Value<? extends java.lang.Number> value)
abstract Value<V>	Value.add(Value<? extends java.lang.Number> value)
abstract Vector<V>	Vector.add(Value<? extends java.lang.Number> value)
int	DoubleValue.compareTo(Value<java.lang.Double> that)
int	FloatValue.compareTo(Value<java.lang.Float> that)
<V extends java.lang.Number> int	Classification.Type.compareValues(Value<V> left, Value<V> right)
static <V extends java.lang.Number> Value<V>	NormalizationUtil.denormalize(org.dmg.pmml.NormContinuous normContinuous, Value<V> value)
DoubleValue	DoubleValue.divide(Value<? extends java.lang.Number> value)
FloatValue	FloatValue.divide(Value<? extends java.lang.Number> value)
abstract Value<V>	Value.divide(Value<? extends java.lang.Number> value)
static <V extends java.lang.Number> Value<V>	MeasureUtil.evaluateDistance(ValueFactory<V> valueFactory, org.dmg.pmml.ComparisonMeasure comparisonMeasure, java.util.List<? extends org.dmg.pmml.ComparisonField<?>> comparisonFields, java.util.List<FieldValue> values, java.util.List<FieldValue> referenceValues, Value<V> adjustment)
static <V extends java.lang.Number> java.util.Map<java.lang.String,?>	TargetUtil.evaluateRegression(TargetField targetField, Value<V> value)
static <V extends java.lang.Number> Value<V>	TargetUtil.evaluateRegressionInternal(TargetField targetField, Value<V> value)
static Report	ReportUtil.getReport(Value<?> value)
<V extends java.lang.Number> java.lang.Double	Classification.Type.getValue(Value<V> value)
<V extends java.lang.Number> boolean	Classification.Type.isValidValue(Value<V> value)
DoubleValue	DoubleValue.multiply(Value<? extends java.lang.Number> value)
FloatValue	FloatValue.multiply(Value<? extends java.lang.Number> value)
abstract Value<V>	Value.multiply(Value<? extends java.lang.Number> value)
static <V extends java.lang.Number> Value<V>	NormalizationUtil.normalize(org.dmg.pmml.NormContinuous normContinuous, Value<V> value)
static <V extends java.lang.Number> Value<V>	TargetUtil.processValue(org.dmg.pmml.Target target, Value<V> value)
void	Classification.put(K key, Value<V> value)
void	EntityClassification.put(E entity, K key, Value<V> value)
DoubleValue	DoubleValue.residual(Value<? extends java.lang.Number> value)
FloatValue	FloatValue.residual(Value<? extends java.lang.Number> value)
abstract Value<V>	Value.residual(Value<? extends java.lang.Number> value)
DoubleValue	DoubleValue.subtract(Value<? extends java.lang.Number> value)
FloatValue	FloatValue.subtract(Value<? extends java.lang.Number> value)
abstract Value<V>	Value.subtract(Value<? extends java.lang.Number> value)

Method parameters in org.jpmml.evaluator with type arguments of type Value

Modifier and Type	Method	Description
protected java.util.Map<K,Value<V>>	KeyValueAggregator.asTransformedMap(com.google.common.base.Function<Vector<V>,Value<V>> function)
static <K,V extends java.lang.Number> java.util.Map.Entry<K,Value<V>>	Classification.getWinner(Classification.Type type, java.util.Collection<java.util.Map.Entry<K,Value<V>>> entries)
static <K,V extends java.lang.Number> java.util.List<java.util.Map.Entry<K,Value<V>>>	Classification.getWinnerList(Classification.Type type, java.util.Collection<java.util.Map.Entry<K,Value<V>>> entries)
static <V extends java.lang.Number> void	ValueUtil.normalizeSimpleMax(java.lang.Iterable<Value<V>> values)
static <V extends java.lang.Number> void	ValueUtil.normalizeSoftMax(java.lang.Iterable<Value<V>> values)
static <V extends java.lang.Number> Value<V>	ValueUtil.sum(java.lang.Iterable<Value<V>> values)

Constructors in org.jpmml.evaluator with parameters of type Value

Constructor	Description
Regression(Value<V> value)

Constructor parameters in org.jpmml.evaluator with type arguments of type Value

Constructor	Description
ValueMap(java.util.Map<K,Value<V>> map)

Uses of Value in org.jpmml.evaluator.clustering

Methods in org.jpmml.evaluator.clustering with parameters of type Value

Modifier and Type	Method	Description
void	ClusterAffinityDistribution.put(org.dmg.pmml.clustering.Cluster entity, Value<V> value)

Uses of Value in org.jpmml.evaluator.general_regression

Methods in org.jpmml.evaluator.general_regression that return Value

Modifier and Type	Method	Description
static <V extends java.lang.Number> Value<V>	GeneralRegressionModelUtil.computeCumulativeLink(org.dmg.pmml.general_regression.GeneralRegressionModel.CumulativeLinkFunction cumulativeLinkFunction, Value<V> value)
static <V extends java.lang.Number> Value<V>	GeneralRegressionModelUtil.computeLink(org.dmg.pmml.general_regression.GeneralRegressionModel.LinkFunction linkFunction, java.lang.Number distParameter, java.lang.Number linkParameter, Value<V> value)

Methods in org.jpmml.evaluator.general_regression with parameters of type Value

Modifier and Type	Method	Description
static <V extends java.lang.Number> Value<V>	GeneralRegressionModelUtil.computeCumulativeLink(org.dmg.pmml.general_regression.GeneralRegressionModel.CumulativeLinkFunction cumulativeLinkFunction, Value<V> value)
static <V extends java.lang.Number> Value<V>	GeneralRegressionModelUtil.computeLink(org.dmg.pmml.general_regression.GeneralRegressionModel.LinkFunction linkFunction, java.lang.Number distParameter, java.lang.Number linkParameter, Value<V> value)

Uses of Value in org.jpmml.evaluator.mining

Methods in org.jpmml.evaluator.mining that return Value

Modifier and Type	Method	Description
static <V extends java.lang.Number> Value<V>	MiningModelUtil.aggregateValues(ValueFactory<V> valueFactory, org.dmg.pmml.mining.Segmentation.MultipleModelMethod multipleModelMethod, org.dmg.pmml.mining.Segmentation.MissingPredictionTreatment missingPredictionTreatment, java.lang.Number missingThreshold, java.util.List<SegmentResult> segmentResults)

Uses of Value in org.jpmml.evaluator.neural_network

Methods in org.jpmml.evaluator.neural_network that return Value

Modifier and Type	Method	Description
static <V extends java.lang.Number> Value<V>	NeuralNetworkUtil.activateNeuronOutput(org.dmg.pmml.neural_network.NeuralNetwork.ActivationFunction activationFunction, java.lang.Number threshold, java.lang.Number leakage, Value<V> value)

Methods in org.jpmml.evaluator.neural_network that return types with arguments of type Value

Modifier and Type	Method	Description
static <V extends java.lang.Number> java.util.Collection<Value<V>>	NeuralNetworkUtil.normalizeNeuralLayerOutputs(org.dmg.pmml.neural_network.NeuralNetwork.NormalizationMethod normalizationMethod, java.util.Collection<Value<V>> values)

Methods in org.jpmml.evaluator.neural_network with parameters of type Value

Modifier and Type	Method	Description
static <V extends java.lang.Number> Value<V>	NeuralNetworkUtil.activateNeuronOutput(org.dmg.pmml.neural_network.NeuralNetwork.ActivationFunction activationFunction, java.lang.Number threshold, java.lang.Number leakage, Value<V> value)

Method parameters in org.jpmml.evaluator.neural_network with type arguments of type Value

Modifier and Type	Method	Description
static <V extends java.lang.Number> java.util.Collection<Value<V>>	NeuralNetworkUtil.normalizeNeuralLayerOutputs(org.dmg.pmml.neural_network.NeuralNetwork.NormalizationMethod normalizationMethod, java.util.Collection<Value<V>> values)

Uses of Value in org.jpmml.evaluator.regression

Methods in org.jpmml.evaluator.regression that return Value

Modifier and Type	Method	Description
static <V extends java.lang.Number> Value<V>	RegressionModelUtil.normalizeBinaryLogisticClassificationResult(org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, Value<V> value)
static <V extends java.lang.Number> Value<V>	RegressionModelUtil.normalizeRegressionResult(org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, Value<V> value)

Methods in org.jpmml.evaluator.regression with parameters of type Value

Modifier and Type	Method	Description
static <V extends java.lang.Number> Value<V>	RegressionModelUtil.normalizeBinaryLogisticClassificationResult(org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, Value<V> value)
static <V extends java.lang.Number> Value<V>	RegressionModelUtil.normalizeRegressionResult(org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, Value<V> value)

Uses of Value in org.jpmml.evaluator.scorecard

Constructors in org.jpmml.evaluator.scorecard with parameters of type Value

Constructor	Description
ScorecardScore(Value<V> value, java.util.List<PartialScore> partialScores)

Uses of Value in org.jpmml.evaluator.support_vector_machine

Methods in org.jpmml.evaluator.support_vector_machine that return Value

Modifier and Type	Method	Description
static <V extends java.lang.Number> Value<V>	KernelUtil.evaluate(org.dmg.pmml.support_vector_machine.Kernel kernel, ValueFactory<V> valueFactory, java.lang.Object input, java.lang.Object vector)
static <V extends java.lang.Number> Value<V>	KernelUtil.evaluateLinearKernel(org.dmg.pmml.support_vector_machine.LinearKernel linearKernel, ValueFactory<V> valueFactory, java.lang.Object input, java.lang.Object vector)
static <V extends java.lang.Number> Value<V>	KernelUtil.evaluatePolynomialKernel(org.dmg.pmml.support_vector_machine.PolynomialKernel polynomialKernel, ValueFactory<V> valueFactory, java.lang.Object input, java.lang.Object vector)
static <V extends java.lang.Number> Value<V>	KernelUtil.evaluateRadialBasisKernel(org.dmg.pmml.support_vector_machine.RadialBasisKernel radialBasisKernel, ValueFactory<V> valueFactory, java.lang.Object input, java.lang.Object vector)
static <V extends java.lang.Number> Value<V>	KernelUtil.evaluateSigmoidKernel(org.dmg.pmml.support_vector_machine.SigmoidKernel sigmoidKernel, ValueFactory<V> valueFactory, java.lang.Object input, java.lang.Object vector)