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.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(Number value)
abstract Value<V>	Value.add(Number coefficient, Number factor)	Adds coefficient * factor.
abstract Value<V>	Value.add(Number coefficient, Number... factors)	Adds coefficient * product(factors).
abstract Value<V>	Value.add(Number coefficient, Number factor, int exponent)	Adds coefficient * (factor ^ exponent).
abstract Value<V>	Value.add(Number coefficient, Number firstFactor, Number secondFactor)
abstract Value<V>	Value.add(Value<? extends Number> value)
abstract Value<V>	Value.arctan()
Value<V>	ValueAggregator.average()
static <V extends Number> Value<V>	MeasureUtil.calculateAdjustment(ValueFactory<V> valueFactory, List<FieldValue> values)
static <V extends Number> Value<V>	MeasureUtil.calculateAdjustment(ValueFactory<V> valueFactory, List<FieldValue> values, List<? extends Number> adjustmentValues)
abstract Value<V>	Value.ceiling()
abstract Value<V>	Value.copy()
abstract Value<V>	Value.cos()
static <V extends Number> Value<V>	NormalizationUtil.denormalize(org.dmg.pmml.NormContinuous normContinuous, Value<V> value)
abstract Value<V>	Value.denormalize(Number leftOrig, Number leftNorm, Number rightOrig, Number rightNorm)
abstract Value<V>	Value.divide(Number value)
abstract Value<V>	Value.divide(Value<? extends Number> value)
abstract Value<V>	Value.elliott()
static <V extends Number> Value<V>	MeasureUtil.evaluateDistance(ValueFactory<V> valueFactory, org.dmg.pmml.ComparisonMeasure comparisonMeasure, List<? extends org.dmg.pmml.ComparisonField<?>> comparisonFields, List<FieldValue> values, List<FieldValue> referenceValues, Value<V> adjustment)
static <V extends Number> Value<V>	TargetUtil.evaluateRegressionInternal(TargetField targetField, Value<V> value)
static <V extends Number> Value<V>	MeasureUtil.evaluateSimilarity(ValueFactory<V> valueFactory, org.dmg.pmml.ComparisonMeasure comparisonMeasure, List<? extends org.dmg.pmml.ComparisonField<?>> comparisonFields, BitSet flags, BitSet referenceFlags)
abstract Value<V>	Value.exp()
abstract Value<V>	Value.floor()
abstract Value<V>	Value.gauss()
abstract Value<V>	Value.gaussSim(Number value)
Value<Double>	DoubleVector.get(int index)
Value<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(Number value)
abstract Value<V>	Value.inverseOddspower(Number value)
abstract Value<V>	Value.inversePower(Number value)
abstract Value<V>	Value.inverseProbit()
abstract Value<V>	Value.ln()
Value<Double>	DoubleVector.max()
Value<Float>	FloatVector.max()
abstract Value<V>	Vector.max()
Value<Double>	DoubleVector.median()
Value<Float>	FloatVector.median()
Value<V>	ValueAggregator.median()
abstract Value<V>	Vector.median()
abstract Value<V>	Value.multiply(Number value)
abstract Value<V>	Value.multiply(Number factor, Number exponent)	Multiplies by factor ^ exponent.
abstract Value<V>	Value.multiply(Value<? extends Number> value)
abstract Value<V>	ValueFactory.newValue()	Creates a value, which is "silently" set to the zero value.
abstract Value<V>	ValueFactory.newValue(Number value)	Creates a value, which is "vocally" set to the specified value.
abstract Value<V>	ValueFactory.newValue(String value)	Creates a value, which is "vocally" set to the specified value.
static <V extends Number> Value<V>	NormalizationUtil.normalize(org.dmg.pmml.NormContinuous normContinuous, Value<V> value)
abstract Value<V>	Value.normalize(Number leftOrig, Number leftNorm, Number rightOrig, Number rightNorm)
abstract Value<V>	Value.power(Number value)
static <V extends 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(Number value)
abstract Value<V>	Value.residual(Value<? extends Number> value)
abstract Value<V>	Value.restrict(Number lowValue, Number highValue)
abstract Value<V>	Value.round()
abstract Value<V>	Value.sin()
abstract Value<V>	Value.square()
abstract Value<V>	Value.subtract(Number value)
abstract Value<V>	Value.subtract(Value<? extends Number> value)
Value<Double>	DoubleVector.sum()
Value<Float>	FloatVector.sum()
Value<V>	ValueAggregator.sum()
static <V extends Number> Value<V>	ValueUtil.sum(Iterable<Value<V>> values)
abstract Value<V>	Vector.sum()
abstract Value<V>	Value.tanh()
abstract Value<V>	Value.threshold(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
static <K,V extends Number> Map.Entry<K,Value<V>>	Classification.getWinner(Classification.Type type, Collection<Map.Entry<K,Value<V>>> entries)
static <K,V extends Number> List<Map.Entry<K,Value<V>>>	Classification.getWinnerList(Classification.Type type, Collection<Map.Entry<K,Value<V>>> entries)
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 Number> value)
FloatVector	ComplexFloatVector.add(Value<? extends Number> value)
DoubleValue	DoubleValue.add(Value<? extends Number> value)
FloatValue	FloatValue.add(Value<? extends Number> value)
DoubleVector	SimpleDoubleVector.add(Value<? extends Number> value)
FloatVector	SimpleFloatVector.add(Value<? extends Number> value)
abstract Value<V>	Value.add(Value<? extends Number> value)
abstract Vector<V>	Vector.add(Value<? extends Number> value)
int	DoubleValue.compareTo(Value<Double> that)
int	FloatValue.compareTo(Value<Float> that)
<V extends Number> int	Classification.Type.compareValues(Value<V> left, Value<V> right)
static <V extends Number> Value<V>	NormalizationUtil.denormalize(org.dmg.pmml.NormContinuous normContinuous, Value<V> value)
DoubleValue	DoubleValue.divide(Value<? extends Number> value)
FloatValue	FloatValue.divide(Value<? extends Number> value)
abstract Value<V>	Value.divide(Value<? extends Number> value)
static <V extends Number> Value<V>	MeasureUtil.evaluateDistance(ValueFactory<V> valueFactory, org.dmg.pmml.ComparisonMeasure comparisonMeasure, List<? extends org.dmg.pmml.ComparisonField<?>> comparisonFields, List<FieldValue> values, List<FieldValue> referenceValues, Value<V> adjustment)
static <V extends Number> Map<String,?>	TargetUtil.evaluateRegression(TargetField targetField, Value<V> value)
static <V extends Number> Value<V>	TargetUtil.evaluateRegressionInternal(TargetField targetField, Value<V> value)
static Report	ReportUtil.getReport(Value<?> value)
<V extends Number> Double	Classification.Type.getValue(Value<V> value)
<V extends Number> boolean	Classification.Type.isValidValue(Value<V> value)
DoubleValue	DoubleValue.multiply(Value<? extends Number> value)
FloatValue	FloatValue.multiply(Value<? extends Number> value)
abstract Value<V>	Value.multiply(Value<? extends Number> value)
static <V extends Number> Value<V>	NormalizationUtil.normalize(org.dmg.pmml.NormContinuous normContinuous, Value<V> value)
static <V extends 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 Number> value)
FloatValue	FloatValue.residual(Value<? extends Number> value)
abstract Value<V>	Value.residual(Value<? extends Number> value)
DoubleValue	DoubleValue.subtract(Value<? extends Number> value)
FloatValue	FloatValue.subtract(Value<? extends Number> value)
abstract Value<V>	Value.subtract(Value<? extends Number> value)

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

Modifier and Type	Method	Description
static <K,V extends Number> Map.Entry<K,Value<V>>	Classification.getWinner(Classification.Type type, Collection<Map.Entry<K,Value<V>>> entries)
static <K,V extends Number> List<Map.Entry<K,Value<V>>>	Classification.getWinnerList(Classification.Type type, Collection<Map.Entry<K,Value<V>>> entries)
static <V extends Number> void	ValueUtil.normalizeSimpleMax(Iterable<Value<V>> values)
static <V extends Number> void	ValueUtil.normalizeSoftMax(Iterable<Value<V>> values)
static <V extends Number> Value<V>	ValueUtil.sum(Iterable<Value<V>> values)

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

Constructor	Description
ValueMap(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 Number> Value<V>	GeneralRegressionModelUtil.computeCumulativeLink(org.dmg.pmml.general_regression.GeneralRegressionModel.CumulativeLinkFunction cumulativeLinkFunction, Value<V> value)
static <V extends Number> Value<V>	GeneralRegressionModelUtil.computeLink(org.dmg.pmml.general_regression.GeneralRegressionModel.LinkFunction linkFunction, Number distParameter, 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 Number> Value<V>	GeneralRegressionModelUtil.computeCumulativeLink(org.dmg.pmml.general_regression.GeneralRegressionModel.CumulativeLinkFunction cumulativeLinkFunction, Value<V> value)
static <V extends Number> Value<V>	GeneralRegressionModelUtil.computeLink(org.dmg.pmml.general_regression.GeneralRegressionModel.LinkFunction linkFunction, Number distParameter, 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 Number> Value<V>	MiningModelUtil.aggregateValues(ValueFactory<V> valueFactory, org.dmg.pmml.mining.Segmentation.MultipleModelMethod multipleModelMethod, org.dmg.pmml.mining.Segmentation.MissingPredictionTreatment missingPredictionTreatment, Number missingThreshold, 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 Number> Value<V>	NeuralNetworkUtil.activateNeuronOutput(org.dmg.pmml.neural_network.NeuralNetwork.ActivationFunction activationFunction, Number threshold, 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 Number> Collection<Value<V>>	NeuralNetworkUtil.normalizeNeuralLayerOutputs(org.dmg.pmml.neural_network.NeuralNetwork.NormalizationMethod normalizationMethod, Collection<Value<V>> values)

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

Modifier and Type	Method	Description
static <V extends Number> Value<V>	NeuralNetworkUtil.activateNeuronOutput(org.dmg.pmml.neural_network.NeuralNetwork.ActivationFunction activationFunction, Number threshold, 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 Number> Collection<Value<V>>	NeuralNetworkUtil.normalizeNeuralLayerOutputs(org.dmg.pmml.neural_network.NeuralNetwork.NormalizationMethod normalizationMethod, 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 Number> Value<V>	RegressionModelUtil.normalizeBinaryLogisticClassificationResult(org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, Value<V> value)
static <V extends 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 Number> Value<V>	RegressionModelUtil.normalizeBinaryLogisticClassificationResult(org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, Value<V> value)
static <V extends Number> Value<V>	RegressionModelUtil.normalizeRegressionResult(org.dmg.pmml.regression.RegressionModel.NormalizationMethod normalizationMethod, Value<V> value)

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