Uses of Interface
it.uniroma2.sag.kelp.data.label.Label

Packages that use Label

Package	Description
it.uniroma2.sag.kelp.data.dataset
it.uniroma2.sag.kelp.data.example
it.uniroma2.sag.kelp.data.label
it.uniroma2.sag.kelp.learningalgorithm
it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm
it.uniroma2.sag.kelp.learningalgorithm.classification.dcd
it.uniroma2.sag.kelp.learningalgorithm.classification.hmm
it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear
it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear.solver
it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm
it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm.solver
it.uniroma2.sag.kelp.learningalgorithm.classification.multiclassification
it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive
it.uniroma2.sag.kelp.learningalgorithm.classification.pegasos
it.uniroma2.sag.kelp.learningalgorithm.classification.perceptron
it.uniroma2.sag.kelp.learningalgorithm.classification.scw
it.uniroma2.sag.kelp.learningalgorithm.regression.liblinear
it.uniroma2.sag.kelp.learningalgorithm.regression.libsvm
it.uniroma2.sag.kelp.learningalgorithm.regression.passiveaggressive
it.uniroma2.sag.kelp.predictionfunction
it.uniroma2.sag.kelp.predictionfunction.classifier
it.uniroma2.sag.kelp.predictionfunction.classifier.multiclass
it.uniroma2.sag.kelp.predictionfunction.model
it.uniroma2.sag.kelp.predictionfunction.regressionfunction
it.uniroma2.sag.kelp.utils.evaluation

Uses of Label in it.uniroma2.sag.kelp.data.dataset

Methods in it.uniroma2.sag.kelp.data.dataset that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	SimpleDataset.getClassificationLabels()
List<Label>	SequenceDataset.getClassificationLabels()
List<Label>	Dataset.getClassificationLabels() Returns all the classification labels in the dataset.
List<Label>	SimpleDataset.getRegressionProperties()
List<Label>	Dataset.getRegressionProperties() Returns all the regression properties in the dataset.

Methods in it.uniroma2.sag.kelp.data.dataset with parameters of type Label

Modifier and Type	Method and Description
int	SimpleDataset.getNumberOfNegativeExamples(Label positiveClass)
int	Dataset.getNumberOfNegativeExamples(Label positiveClass) Returns the number of negative Examples of a given class
int	SimpleDataset.getNumberOfPositiveExamples(Label positiveClass)
int	Dataset.getNumberOfPositiveExamples(Label positiveClass) Returns the number of positive Examples of a given class

Method parameters in it.uniroma2.sag.kelp.data.dataset with type arguments of type Label

Modifier and Type	Method and Description
static Dataset	SimpleDataset.extractExamplesOfClasses(Dataset dataset, List<Label> labels) This method extracts examples of given labels from dataset

Uses of Label in it.uniroma2.sag.kelp.data.example

Methods in it.uniroma2.sag.kelp.data.example that return Label

Modifier and Type	Method and Description
Label	SequencePath.getAssignedLabel(int i)
Label[]	Example.getLabels() Returns the classification classificationLabels of this example

Methods in it.uniroma2.sag.kelp.data.example that return types with arguments of type Label

Modifier and Type	Method and Description
HashSet<Label>	SequenceExample.getClassificationLabels()
HashSet<Label>	Example.getClassificationLabels()

Methods in it.uniroma2.sag.kelp.data.example with parameters of type Label

Modifier and Type	Method and Description
void	Example.addLabel(Label label) Adds a label to the example
Float	Example.getRegressionValue(Label property) Returns the numeric value associated to a label
boolean	Example.isExampleOf(Label label) Asserts whether this is a positive example for the input label or not
void	Example.setLabels(Label[] labels) Sets the example classificationLabels

Method parameters in it.uniroma2.sag.kelp.data.example with type arguments of type Label

Modifier and Type	Method and Description
void	Example.setClassificationLabels(HashSet<Label> labels)

Constructors in it.uniroma2.sag.kelp.data.example with parameters of type Label

Constructor and Description
SimpleExample(Label[] labels, HashMap<String,Representation> representations) Initializes a SimpleExample with the input representations and labels

Uses of Label in it.uniroma2.sag.kelp.data.label

Classes in it.uniroma2.sag.kelp.data.label that implement Label

Modifier and Type	Class and Description
class	NumericLabel It value consisting of a real value.
class	StringLabel It is a label consisting of an String value.

Methods in it.uniroma2.sag.kelp.data.label that return Label

Modifier and Type	Method and Description
Label	SequenceEmission.getLabel()
Label	NumericLabel.getProperty() Returns the property
static Label	LabelFactory.parseLabel(String labelDescription) Initializes and returns the label described in labelDescription

Methods in it.uniroma2.sag.kelp.data.label with parameters of type Label

Modifier and Type	Method and Description
void	SequenceEmission.setLabel(Label label)
void	NumericLabel.setProperty(Label property)

Constructors in it.uniroma2.sag.kelp.data.label with parameters of type Label

Constructor and Description
NumericLabel(Label property, float labelValue) Initializes a NumericLabel whose value is labelValue and whose name is name
SequenceEmission(Label label, float emission)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm

Fields in it.uniroma2.sag.kelp.learningalgorithm declared as Label

Modifier and Type	Field and Description
protected Label	PassiveAggressive.label

Methods in it.uniroma2.sag.kelp.learningalgorithm that return Label

Modifier and Type	Method and Description
Label	PassiveAggressive.getLabel()
Label	BinaryLearningAlgorithm.getLabel()

Methods in it.uniroma2.sag.kelp.learningalgorithm that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	PassiveAggressive.getLabels()
List<Label>	MultiEpochLearning.getLabels()
List<Label>	LearningAlgorithm.getLabels() Returns the labels representing the concept to be learned.
List<Label>	BinaryLearningAlgorithm.getLabels()

Methods in it.uniroma2.sag.kelp.learningalgorithm with parameters of type Label

Modifier and Type	Method and Description
void	PassiveAggressive.setLabel(Label label)
void	BinaryLearningAlgorithm.setLabel(Label label)

Method parameters in it.uniroma2.sag.kelp.learningalgorithm with type arguments of type Label

Modifier and Type	Method and Description
void	PassiveAggressive.setLabels(List<Label> labels)
void	MultiEpochLearning.setLabels(List<Label> labels)
void	LearningAlgorithm.setLabels(List<Label> labels) Sets the labels representing the concept to be learned.
void	BinaryLearningAlgorithm.setLabels(List<Label> labels)

Constructor parameters in it.uniroma2.sag.kelp.learningalgorithm with type arguments of type Label

Constructor and Description
MultiEpochLearning(int epochs, LearningAlgorithm baseAlgorithm, List<Label> labels)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm

Fields in it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm declared as Label

Modifier and Type	Field and Description
protected Label	BudgetedLearningAlgorithm.label

Methods in it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm that return Label

Modifier and Type	Method and Description
Label	BudgetedLearningAlgorithm.getLabel()

Methods in it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	BudgetedLearningAlgorithm.getLabels()

Methods in it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm with parameters of type Label

Modifier and Type	Method and Description
void	BudgetedLearningAlgorithm.setLabel(Label label)

Method parameters in it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm with type arguments of type Label

Modifier and Type	Method and Description
void	BudgetedLearningAlgorithm.setLabels(List<Label> labels)

Constructors in it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm with parameters of type Label

Constructor and Description
RandomizedBudgetPerceptron(int budget, OnlineLearningAlgorithm baseAlgorithm, long seed, Label label)
Stoptron(int budget, OnlineLearningAlgorithm baseAlgorithm, Label label)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.classification.dcd

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.dcd that return Label

Modifier and Type	Method and Description
Label	DCDLearningAlgorithm.getLabel()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.dcd that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	DCDLearningAlgorithm.getLabels()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.dcd with parameters of type Label

Modifier and Type	Method and Description
void	DCDLearningAlgorithm.setLabel(Label label)

Method parameters in it.uniroma2.sag.kelp.learningalgorithm.classification.dcd with type arguments of type Label

Modifier and Type	Method and Description
void	DCDLearningAlgorithm.setLabels(List<Label> labels)

Constructors in it.uniroma2.sag.kelp.learningalgorithm.classification.dcd with parameters of type Label

Constructor and Description
DCDLearningAlgorithm(Label label, double cp, double cn, DCDLoss dcdLoss, boolean useBias, int maxIterations, String representationName)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.classification.hmm

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.hmm that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	SequenceClassificationLearningAlgorithm.getLabels()

Method parameters in it.uniroma2.sag.kelp.learningalgorithm.classification.hmm with type arguments of type Label

Modifier and Type	Method and Description
void	SequenceClassificationLearningAlgorithm.setLabels(List<Label> labels)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear that return Label

Modifier and Type	Method and Description
Label	LibLinearLearningAlgorithm.getLabel()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	LibLinearLearningAlgorithm.getLabels()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear with parameters of type Label

Modifier and Type	Method and Description
void	LibLinearLearningAlgorithm.setLabel(Label label)

Method parameters in it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear with type arguments of type Label

Modifier and Type	Method and Description
void	LibLinearLearningAlgorithm.setLabels(List<Label> labels)

Constructors in it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear with parameters of type Label

Constructor and Description
LibLinearLearningAlgorithm(Label label, double cp, double cn, boolean fairness, String representationName)
LibLinearLearningAlgorithm(Label label, double cp, double cn, String representationName)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear.solver

Constructors in it.uniroma2.sag.kelp.learningalgorithm.classification.liblinear.solver with parameters of type Label

Constructor and Description
Problem(Dataset dataset, String reprentationName, Label label, Problem.LibLinearSolverType solverType)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm

Constructors in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm with parameters of type Label

Constructor and Description
BinaryCSvmClassification(Kernel kernel, Label label, float cp, float cn)
BinaryCSvmClassification(Kernel kernel, Label label, float cp, float cn, boolean useFairness)
BinaryNuSvmClassification(Kernel kernel, Label label, float nu)
OneClassSvmClassification(Kernel kernel, Label label, float nu)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm.solver

Fields in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm.solver declared as Label

Modifier and Type	Field and Description
protected Label	LibSvmSolver.label The label to be learned by the classifier

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm.solver that return Label

Modifier and Type	Method and Description
Label	LibSvmSolver.getLabel()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm.solver that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	LibSvmSolver.getLabels()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm.solver with parameters of type Label

Modifier and Type	Method and Description
void	LibSvmSolver.setLabel(Label label)

Method parameters in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm.solver with type arguments of type Label

Modifier and Type	Method and Description
void	LibSvmSolver.setLabels(List<Label> labels)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.classification.multiclassification

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.multiclassification that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	OneVsOneLearning.getLabels() Returns the labels to be learned applying a one-vs-one strategy
List<Label>	OneVsAllLearning.getLabels() Returns the labels to be learned applying a one-vs-all strategy
List<Label>	MultiLabelClassificationLearning.getLabels() Returns the labels to be learned

Method parameters in it.uniroma2.sag.kelp.learningalgorithm.classification.multiclassification with type arguments of type Label

Modifier and Type	Method and Description
void	OneVsOneLearning.setLabels(List<Label> labels) Set the labels associated to this multi-classifier.
void	OneVsAllLearning.setLabels(List<Label> labels) Set the labels associated to this multi-classifier.
void	MultiLabelClassificationLearning.setLabels(List<Label> labels) Set the labels associated to this multi-classifier.

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive

Constructors in it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive with parameters of type Label

Constructor and Description
BudgetedPassiveAggressiveClassification(int budget, Kernel kernel, float c, boolean fairness, BudgetedPassiveAggressiveClassification.DeletingPolicy deletingPolicy, Label label)
BudgetedPassiveAggressiveClassification(int budget, Kernel kernel, float cp, float cn, BudgetedPassiveAggressiveClassification.DeletingPolicy deletingPolicy, Label label)
KernelizedPassiveAggressiveClassification(float cp, float cn, PassiveAggressiveClassification.Loss loss, PassiveAggressive.Policy policy, Kernel kernel, Label label)
LinearPassiveAggressiveClassification(float cp, float cn, PassiveAggressiveClassification.Loss loss, PassiveAggressive.Policy policy, String representation, Label label)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.classification.pegasos

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.pegasos that return Label

Modifier and Type	Method and Description
Label	PegasosLearningAlgorithm.getLabel()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.pegasos that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	PegasosLearningAlgorithm.getLabels()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.pegasos with parameters of type Label

Modifier and Type	Method and Description
void	PegasosLearningAlgorithm.setLabel(Label label)

Method parameters in it.uniroma2.sag.kelp.learningalgorithm.classification.pegasos with type arguments of type Label

Modifier and Type	Method and Description
void	PegasosLearningAlgorithm.setLabels(List<Label> labels)

Constructors in it.uniroma2.sag.kelp.learningalgorithm.classification.pegasos with parameters of type Label

Constructor and Description
PegasosLearningAlgorithm(int k, float lambda, int T, String Representation, Label label)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.classification.perceptron

Fields in it.uniroma2.sag.kelp.learningalgorithm.classification.perceptron declared as Label

Modifier and Type	Field and Description
protected Label	Perceptron.label

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.perceptron that return Label

Modifier and Type	Method and Description
Label	Perceptron.getLabel()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.perceptron that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	Perceptron.getLabels()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.perceptron with parameters of type Label

Modifier and Type	Method and Description
void	Perceptron.setLabel(Label label)

Method parameters in it.uniroma2.sag.kelp.learningalgorithm.classification.perceptron with type arguments of type Label

Modifier and Type	Method and Description
void	Perceptron.setLabels(List<Label> labels)

Constructors in it.uniroma2.sag.kelp.learningalgorithm.classification.perceptron with parameters of type Label

Constructor and Description
KernelizedPerceptron(float alpha, float margin, boolean unbiased, Kernel kernel, Label label)
LinearPerceptron(float alpha, float margin, boolean unbiased, String representation, Label label)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.classification.scw

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.scw that return Label

Modifier and Type	Method and Description
Label	SoftConfidenceWeightedClassification.getLabel()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.scw that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	SoftConfidenceWeightedClassification.getLabels()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.scw with parameters of type Label

Modifier and Type	Method and Description
void	SoftConfidenceWeightedClassification.setLabel(Label label)

Method parameters in it.uniroma2.sag.kelp.learningalgorithm.classification.scw with type arguments of type Label

Modifier and Type	Method and Description
void	SoftConfidenceWeightedClassification.setLabels(List<Label> labels)

Constructors in it.uniroma2.sag.kelp.learningalgorithm.classification.scw with parameters of type Label

Constructor and Description
SoftConfidenceWeightedClassification(Label label, SCWType scwType, float eta, float cp, float cn, boolean fairness, String representationName)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.regression.liblinear

Methods in it.uniroma2.sag.kelp.learningalgorithm.regression.liblinear that return Label

Modifier and Type	Method and Description
Label	LibLinearRegression.getLabel()

Methods in it.uniroma2.sag.kelp.learningalgorithm.regression.liblinear that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	LibLinearRegression.getLabels()

Methods in it.uniroma2.sag.kelp.learningalgorithm.regression.liblinear with parameters of type Label

Modifier and Type	Method and Description
void	LibLinearRegression.setLabel(Label label)

Method parameters in it.uniroma2.sag.kelp.learningalgorithm.regression.liblinear with type arguments of type Label

Modifier and Type	Method and Description
void	LibLinearRegression.setLabels(List<Label> labels)

Constructors in it.uniroma2.sag.kelp.learningalgorithm.regression.liblinear with parameters of type Label

Constructor and Description
LibLinearRegression(Label label, double c, double p, String representationName)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.regression.libsvm

Methods in it.uniroma2.sag.kelp.learningalgorithm.regression.libsvm with parameters of type Label

Modifier and Type	Method and Description
void	EpsilonSvmRegression.setLabels(Label... labels)

Constructors in it.uniroma2.sag.kelp.learningalgorithm.regression.libsvm with parameters of type Label

Constructor and Description
EpsilonSvmRegression(Kernel kernel, Label label, float c, float pReg)

Uses of Label in it.uniroma2.sag.kelp.learningalgorithm.regression.passiveaggressive

Constructors in it.uniroma2.sag.kelp.learningalgorithm.regression.passiveaggressive with parameters of type Label

Constructor and Description
KernelizedPassiveAggressiveRegression(float aggressiveness, float epsilon, PassiveAggressive.Policy policy, Kernel kernel, Label label)
LinearPassiveAggressiveRegression(float aggressiveness, float epsilon, PassiveAggressive.Policy policy, String representation, Label label)

Uses of Label in it.uniroma2.sag.kelp.predictionfunction

Methods in it.uniroma2.sag.kelp.predictionfunction that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	SequencePredictionFunction.getLabels()
List<Label>	PredictionFunction.getLabels() Returns the labels representing the concept to be predicted.

Methods in it.uniroma2.sag.kelp.predictionfunction with parameters of type Label

Modifier and Type	Method and Description
Float	SequencePrediction.getScore(Label label)
Float	Prediction.getScore(Label label) Return the prediction score associated to a given label

Method parameters in it.uniroma2.sag.kelp.predictionfunction with type arguments of type Label

Modifier and Type	Method and Description
void	SequencePredictionFunction.setLabels(List<Label> labels)
void	PredictionFunction.setLabels(List<Label> labels) Sets the labels representing the concept to be predicted.

Uses of Label in it.uniroma2.sag.kelp.predictionfunction.classifier

Fields in it.uniroma2.sag.kelp.predictionfunction.classifier declared as Label

Modifier and Type	Field and Description
protected Label	BinaryClassifier.positiveClass

Methods in it.uniroma2.sag.kelp.predictionfunction.classifier that return Label

Modifier and Type	Method and Description
Label	BinaryClassifier.getLabel()

Methods in it.uniroma2.sag.kelp.predictionfunction.classifier that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	ClassificationOutput.getAllClasses() Returns all the classes involved in the classification process (both predicted and not)
List<Label>	BinaryMarginClassifierOutput.getAllClasses()
List<Label>	BinaryClassifier.getLabels()
List<Label>	ClassificationOutput.getPredictedClasses() Returns all the classes that the classifier has predicted
List<Label>	BinaryMarginClassifierOutput.getPredictedClasses()

Methods in it.uniroma2.sag.kelp.predictionfunction.classifier with parameters of type Label

Modifier and Type	Method and Description
Float	BinaryMarginClassifierOutput.getScore(Label label)
boolean	ClassificationOutput.isClassPredicted(Label label) Returns a boolean identifying the predicted membership to a specified class
boolean	BinaryMarginClassifierOutput.isClassPredicted(Label label)
void	BinaryClassifier.setLabel(Label label)

Method parameters in it.uniroma2.sag.kelp.predictionfunction.classifier with type arguments of type Label

Modifier and Type	Method and Description
void	BinaryClassifier.setLabels(List<Label> labels)

Constructors in it.uniroma2.sag.kelp.predictionfunction.classifier with parameters of type Label

Constructor and Description
BinaryKernelMachineClassifier(BinaryKernelMachineModel model, Label label)
BinaryMarginClassifierOutput(Label positiveClass, float prediction)

Uses of Label in it.uniroma2.sag.kelp.predictionfunction.classifier.multiclass

Methods in it.uniroma2.sag.kelp.predictionfunction.classifier.multiclass that return Label

Modifier and Type	Method and Description
Label[]	OneVsOneClassifier.getNegativeLabelsForClassifier() Return the negative labels associated to each classifier

Methods in it.uniroma2.sag.kelp.predictionfunction.classifier.multiclass that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	OneVsOneClassificationOutput.getAllClasses()
List<Label>	OneVsAllClassificationOutput.getAllClasses()
List<Label>	MultiLabelClassificationOutput.getAllClasses()
HashMap<Label,Integer>	OneVsOneClassificationOutput.getCounter()
List<Label>	OneVsOneClassifier.getLabels()
List<Label>	OneVsAllClassifier.getLabels()
List<Label>	MultiLabelClassifier.getLabels()
HashMap<Label,Float>	OneVsOneClassificationOutput.getMaxMarginForLabel()
List<Label>	OneVsOneClassificationOutput.getPredictedClasses()
List<Label>	OneVsAllClassificationOutput.getPredictedClasses()
List<Label>	MultiLabelClassificationOutput.getPredictedClasses()

Methods in it.uniroma2.sag.kelp.predictionfunction.classifier.multiclass with parameters of type Label

Modifier and Type	Method and Description
void	OneVsAllClassificationOutput.addBinaryPrediction(Label label, float prediction) Sets the score associated to a given class
void	MultiLabelClassificationOutput.addBinaryPrediction(Label label, float prediction) Sets the score associated to a given class
void	OneVsOneClassificationOutput.addVotedPrediction(Label l, float score)
Float	OneVsOneClassificationOutput.getScore(Label label)
Float	OneVsAllClassificationOutput.getScore(Label label)
Float	MultiLabelClassificationOutput.getScore(Label label)
boolean	OneVsOneClassificationOutput.isClassPredicted(Label label)
boolean	OneVsAllClassificationOutput.isClassPredicted(Label label)
boolean	MultiLabelClassificationOutput.isClassPredicted(Label label)
void	OneVsOneClassifier.setNegativeLabelsForClassifier(Label[] negativeLabelsForClassifier) Set the negative label classifier array

Method parameters in it.uniroma2.sag.kelp.predictionfunction.classifier.multiclass with type arguments of type Label

Modifier and Type	Method and Description
void	OneVsOneClassifier.setLabels(List<Label> labels)
void	OneVsAllClassifier.setLabels(List<Label> labels)
void	MultiLabelClassifier.setLabels(List<Label> labels)

Uses of Label in it.uniroma2.sag.kelp.predictionfunction.model

Fields in it.uniroma2.sag.kelp.predictionfunction.model with type parameters of type Label

Modifier and Type	Field and Description
protected List<Label>	MulticlassModel.labels

Methods in it.uniroma2.sag.kelp.predictionfunction.model that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	MulticlassModel.getLabels()

Method parameters in it.uniroma2.sag.kelp.predictionfunction.model with type arguments of type Label

Modifier and Type	Method and Description
void	MulticlassModel.setLabels(List<Label> labels)

Uses of Label in it.uniroma2.sag.kelp.predictionfunction.regressionfunction

Fields in it.uniroma2.sag.kelp.predictionfunction.regressionfunction declared as Label

Modifier and Type	Field and Description
protected Label	UnivariateRegressionFunction.property

Methods in it.uniroma2.sag.kelp.predictionfunction.regressionfunction that return types with arguments of type Label

Modifier and Type	Method and Description
List<Label>	UnivariateRegressionOutput.getAllProperties()
List<Label>	RegressionOutput.getAllProperties() Returns all the properties on which the regressor has to provide predictions
List<Label>	UnivariateRegressionFunction.getLabels()

Methods in it.uniroma2.sag.kelp.predictionfunction.regressionfunction with parameters of type Label

Modifier and Type	Method and Description
Float	UnivariateRegressionOutput.getScore(Label label)

Method parameters in it.uniroma2.sag.kelp.predictionfunction.regressionfunction with type arguments of type Label

Modifier and Type	Method and Description
void	UnivariateRegressionFunction.setLabels(List<Label> labels)

Constructors in it.uniroma2.sag.kelp.predictionfunction.regressionfunction with parameters of type Label

Constructor and Description
UnivariateRegressionOutput(Label property, float predictedValue)

Uses of Label in it.uniroma2.sag.kelp.utils.evaluation

Fields in it.uniroma2.sag.kelp.utils.evaluation with type parameters of type Label

Modifier and Type	Field and Description
protected HashMap<Label,MulticlassClassificationEvaluator.ClassStats>	MulticlassClassificationEvaluator.classStats
protected List<Label>	MulticlassClassificationEvaluator.labels

Methods in it.uniroma2.sag.kelp.utils.evaluation with parameters of type Label

Modifier and Type	Method and Description
float	MulticlassClassificationEvaluator.getF1For(Label l) Return the f1 for the specified label
float	MulticlassClassificationEvaluator.getFnFor(Label l) Return the false negatives for the specified label
float	MulticlassClassificationEvaluator.getFpFor(Label l) Return the false positives for the specified label
float	RegressorEvaluator.getMeanSquaredError(Label label) Returns the mean square error of the Label label.
float	MulticlassClassificationEvaluator.getPrecisionFor(Label l) Return the precision for the specified label
float	MulticlassClassificationEvaluator.getRecallFor(Label l) Return the recall for the specified label
float	MulticlassClassificationEvaluator.getTnFor(Label l) Return the true negatives for the specified label
float	MulticlassClassificationEvaluator.getTpFor(Label l) Return the true positives for the specified label
void	MulticlassClassificationEvaluator.printCounters(Label l) Print the counters of the specified Label l.

Method parameters in it.uniroma2.sag.kelp.utils.evaluation with type arguments of type Label

Modifier and Type	Method and Description
float	MulticlassClassificationEvaluator.getMeanF1For(ArrayList<Label> ls) Return the mean of the F1 scores considering the specified labels only

Constructors in it.uniroma2.sag.kelp.utils.evaluation with parameters of type Label

Constructor and Description
BinaryClassificationEvaluator(Label positiveClass)

Constructor parameters in it.uniroma2.sag.kelp.utils.evaluation with type arguments of type Label

Constructor and Description
MulticlassClassificationEvaluator(List<Label> labels) Initialize a new F1Evaluator that will work on the specified classes
MulticlassSequenceClassificationEvaluator(List<Label> labels) Initialize a new F1Evaluator that will work on the specified classes
RegressorEvaluator(List<Label> labels)