Uses of Class
it.uniroma2.sag.kelp.kernel.Kernel

Packages that use Kernel

Package	Description
it.uniroma2.sag.kelp.data.manipulator
it.uniroma2.sag.kelp.data.representation.structure.similarity
it.uniroma2.sag.kelp.examples.demo.qc
it.uniroma2.sag.kelp.kernel
it.uniroma2.sag.kelp.kernel.graph
it.uniroma2.sag.kelp.kernel.pairs
it.uniroma2.sag.kelp.kernel.sequence
it.uniroma2.sag.kelp.kernel.standard
it.uniroma2.sag.kelp.kernel.tree
it.uniroma2.sag.kelp.kernel.vector
it.uniroma2.sag.kelp.learningalgorithm
it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm
it.uniroma2.sag.kelp.learningalgorithm.classification.hmm
it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm
it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm.solver
it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive
it.uniroma2.sag.kelp.learningalgorithm.classification.perceptron
it.uniroma2.sag.kelp.learningalgorithm.clustering.kernelbasedkmeans
it.uniroma2.sag.kelp.learningalgorithm.regression.libsvm
it.uniroma2.sag.kelp.learningalgorithm.regression.passiveaggressive
it.uniroma2.sag.kelp.linearization.nystrom
it.uniroma2.sag.kelp.predictionfunction.model

Uses of Kernel in it.uniroma2.sag.kelp.data.manipulator

Constructors in it.uniroma2.sag.kelp.data.manipulator with parameters of type Kernel

Constructor and Description
PairSimilarityExtractor(String similarityVectorName, Kernel... kernel)

Uses of Kernel in it.uniroma2.sag.kelp.data.representation.structure.similarity

Methods in it.uniroma2.sag.kelp.data.representation.structure.similarity that return Kernel

Modifier and Type	Method and Description
Kernel	VectorBasedStructureElementSimilarity.getKernel() Returns the kernel used in comparing two vectors

Methods in it.uniroma2.sag.kelp.data.representation.structure.similarity with parameters of type Kernel

Modifier and Type	Method and Description
void	VectorBasedStructureElementSimilarity.setKernel(Kernel kernel) Sets the kernel to be used in comparing two vectors

Uses of Kernel in it.uniroma2.sag.kelp.examples.demo.qc

Methods in it.uniroma2.sag.kelp.examples.demo.qc that return Kernel

Modifier and Type	Method and Description
static Kernel	QuestionClassification.getQCKernelFunction(SimpleDataset trainingSet, SimpleDataset testSet, String kernelId) Get one of the kernel functions used in the Question Classification examples.

Uses of Kernel in it.uniroma2.sag.kelp.kernel

Subclasses of Kernel in it.uniroma2.sag.kelp.kernel

Modifier and Type	Class and Description
class	DirectKernel<T extends Representation> It is a kernel that operates exploiting directly on a specific representation.
class	KernelCombination It is a kernel that operates combining other kernels
class	KernelComposition It is a kernel that operates enriching the computation performed by another kernel

Fields in it.uniroma2.sag.kelp.kernel declared as Kernel

Modifier and Type	Field and Description
protected Kernel	KernelComposition.baseKernel

Fields in it.uniroma2.sag.kelp.kernel with type parameters of type Kernel

Modifier and Type	Field and Description
protected List<Kernel>	KernelCombination.toCombine

Methods in it.uniroma2.sag.kelp.kernel that return Kernel

Modifier and Type	Method and Description
Kernel	KernelComposition.getBaseKernel() Returns the kernel this kernel is enriching
static Kernel	Kernel.load(String inputFilePath) Load a kernel function from a file path.

Methods in it.uniroma2.sag.kelp.kernel that return types with arguments of type Kernel

Modifier and Type	Method and Description
List<Kernel>	KernelCombination.getToCombine() Returns a list of the kernels this kernel is combining

Methods in it.uniroma2.sag.kelp.kernel with parameters of type Kernel

Modifier and Type	Method and Description
static void	Kernel.save(Kernel kernel, String outputFilePath) Save the input kernel in a file.
void	KernelComposition.setBaseKernel(Kernel baseKernel)

Method parameters in it.uniroma2.sag.kelp.kernel with type arguments of type Kernel

Modifier and Type	Method and Description
void	KernelCombination.setToCombine(List<Kernel> toCombine)

Uses of Kernel in it.uniroma2.sag.kelp.kernel.graph

Subclasses of Kernel in it.uniroma2.sag.kelp.kernel.graph

Modifier and Type	Class and Description
class	ShortestPathKernel Implementation of the Shortest Path Kernel for Graphs Reference paper: [1] K.

Uses of Kernel in it.uniroma2.sag.kelp.kernel.pairs

Subclasses of Kernel in it.uniroma2.sag.kelp.kernel.pairs

Modifier and Type	Class and Description
class	BestPairwiseAlignmentKernel It is a kernel operating on ExamplePairs applying the following formula: \(K( < x_1, x_2 >, < y_1,y_2 > ) = softmax(BK(x_1, y_1) \cdot BK(x_2, y_2) , BK(x_1, y_2) \cdot BK(x_2, y_1))\)
class	KernelOnPairs It is a kernel operating on ExamplePairs applying a simpler kernel to the pair elements
class	PairwiseProductKernel It is a kernel operating on ExamplePairs applying the following formula: \(K( < x_1, x_2 >, < y_1,y_2 > ) = BK(x_1, y_1) \cdot BK(x_2, y_2) + BK(x_1, y_2) \cdot BK(x_2, y_1)\) where BK is another kernel the kernel on pairs relies on.
class	PairwiseSumKernel It is a kernel operating on ExamplePairs applying the following formula: \(K( < x_1, x_2 >, < y_1,y_2 > ) = BK(x_1, y_1) + BK(x_2, y_2) + BK(x_1, y_2) + BK(x_2, y_1)\) where BK is another kernel the kernel on pairs relies on.
class	PreferenceKernel It is a kernel operating on ExamplePairs applying the following formula: \(K( < x_1, x_2 >, < y_1,y_2 > ) = BK(x_1, y_1) + BK(x_2, y_2) - BK(x_1, y_2) - BK(x_2, y_1)\) where BK is another kernel the preference kernel relies on.
class	UncrossedPairwiseProductKernel It is a kernel operating on ExamplePairs applying the following formula: \(K( < x_1, x_2 >, < y_1,y_2 > ) = BK(x_1, y_1) \cdot BK(x_2, y_2)\) where BK is another kernel the kernel on pairs relies on.
class	UncrossedPairwiseSumKernel It is a kernel operating on ExamplePairs applying the following formula: \(K( < x_1, x_2 >, < y_1,y_2 > ) = BK(x_1, y_1) + BK(x_2, y_2)\) where BK is another kernel the kernel on pairs relies on.

Constructors in it.uniroma2.sag.kelp.kernel.pairs with parameters of type Kernel

Constructor and Description
BestPairwiseAlignmentKernel(Kernel baseKernel, boolean intraPairSimProduct) Defines a Kernel operating on pairs that applies the following formula: \(K( < x_1, x_2 >, < y_1,y_2 > ) = softmax(BK(x_1, y_1) \cdot BK(x_2, y_2) , BK(x_1, y_2) \cdot BK(x_2, y_1))\)
PairwiseProductKernel(Kernel baseKernel, boolean intraPairSimProduct) Defines a Kernel operating on pairs that applies the following formula: \(K( < x_1, x_2 >, < y_1,y_2 > ) = BK(x_1, y_1) \cdot BK(x_2, y_2) + BK(x_1, y_2) \cdot BK(x_2, y_1)\)
PairwiseSumKernel(Kernel baseKernel, boolean intraPairSimProduct) Defines a Kernel operating on pairs that applies the following formula: \(K( < x_1, x_2 >, < y_1,y_2 > ) = BK(x_1, y_1) + BK(x_2, y_2) + BK(x_1, y_2) + BK(x_2, y_1)\)
PreferenceKernel(Kernel baseKernel)
UncrossedPairwiseProductKernel(Kernel baseKernel, boolean intraPairSimProduct) Defines a Kernel operating on pairs that applies the following formula: \(K( < x_1, x_2 >, < y_1,y_2 > ) = BK(x_1, y_1) \cdot BK(x_2, y_2)\)
UncrossedPairwiseSumKernel(Kernel baseKernel, boolean intraPairSimProduct) Defines a Kernel operating on pairs that applies the following formula: \(K( < x_1, x_2 >, < y_1,y_2 > ) = BK(x_1, y_1) + BK(x_2, y_2)\)

Uses of Kernel in it.uniroma2.sag.kelp.kernel.sequence

Subclasses of Kernel in it.uniroma2.sag.kelp.kernel.sequence

Modifier and Type	Class and Description
class	SequenceKernel Sequence Kernel implementation.

Uses of Kernel in it.uniroma2.sag.kelp.kernel.standard

Subclasses of Kernel in it.uniroma2.sag.kelp.kernel.standard

Modifier and Type	Class and Description
class	KernelMultiplication Multiplication of Kernels Given the kernels \(K_1 \ldots K_n\), the combination formula is: \(\prod_{i}K_i\)
class	LinearKernelCombination Weighted Linear Combination of Kernels Given the kernels \(K_1 \ldots K_n\), with weights \(c_1 \ldots c_n\), the combination formula is: \(\sum_{i}c_iK_i\)
class	NormalizationKernel Normalization of a generic kernel K Normalization formula: \(K(x,y) = \frac{K(x,y)}{\sqrt{(K(x,x) \cdot K(y,y))}}\)
class	PolynomialKernel
class	RbfKernel Radial Basis Function Kernel.

Methods in it.uniroma2.sag.kelp.kernel.standard with parameters of type Kernel

Modifier and Type	Method and Description
void	LinearKernelCombination.addKernel(float weight, Kernel kernel) Adds a kernel with a corresponding weight to the linear combination of kernels

Constructors in it.uniroma2.sag.kelp.kernel.standard with parameters of type Kernel

Constructor and Description
NormalizationKernel(Kernel kernelToNormalize)
PolynomialKernel(float degree, float a, float b, Kernel inputSpace)
PolynomialKernel(float degree, Kernel inputSpace)
RbfKernel(float gamma, Kernel inputSpace)

Uses of Kernel in it.uniroma2.sag.kelp.kernel.tree

Subclasses of Kernel in it.uniroma2.sag.kelp.kernel.tree

Modifier and Type	Class and Description
class	PartialTreeKernel Partial Tree Kernel implementation.
class	SmoothedPartialTreeKernel Partial Tree Kernel implementation.
class	SubSetTreeKernel A SubSetTree Kernel is a convolution kernel that evaluates the tree fragments shared between two trees.
class	SubTreeKernel SubTree Kernel implementation.

Uses of Kernel in it.uniroma2.sag.kelp.kernel.vector

Subclasses of Kernel in it.uniroma2.sag.kelp.kernel.vector

Modifier and Type	Class and Description
class	LinearKernel Linear Kernel for Vectors It executes the dot product between two Vector representations

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

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

Modifier and Type	Method and Description
Kernel	KernelMethod.getKernel() Returns the kernel exploited by this learner

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

Modifier and Type	Method and Description
void	KernelMethod.setKernel(Kernel kernel) Sets the kernel this

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

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

Modifier and Type	Method and Description
Kernel	Stoptron.getKernel()
Kernel	RandomizedBudgetPerceptron.getKernel()

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

Modifier and Type	Method and Description
void	Stoptron.setKernel(Kernel kernel)
void	RandomizedBudgetPerceptron.setKernel(Kernel kernel)

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

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.hmm that return Kernel

Modifier and Type	Method and Description
Kernel	SequenceClassificationKernelBasedLearningAlgorithm.getKernel()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.hmm with parameters of type Kernel

Modifier and Type	Method and Description
void	SequenceClassificationKernelBasedLearningAlgorithm.setKernel(Kernel kernel)

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

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

Modifier and Type	Method and Description
void	BinaryNuSvmClassification.setKernel(Kernel kernel)
void	BinaryCSvmClassification.setKernel(Kernel kernel)

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

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 Kernel in it.uniroma2.sag.kelp.learningalgorithm.classification.libsvm.solver

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

Modifier and Type	Field and Description
protected Kernel	LibSvmSolver.kernel The Kernel function between examples, i.e.

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

Modifier and Type	Method and Description
Kernel	LibSvmSolver.getKernel()

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

Constructor and Description
LibCSvmSolver(Kernel kernel, float cp, float cn)
LibNuSvmSolver(Kernel kernel, int cp, int cn)
LibSvmSolver(Kernel kernel, float Cp, float Cn)

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

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive that return Kernel

Modifier and Type	Method and Description
Kernel	KernelizedPassiveAggressiveClassification.getKernel()
Kernel	BudgetedPassiveAggressiveClassification.getKernel()

Methods in it.uniroma2.sag.kelp.learningalgorithm.classification.passiveaggressive with parameters of type Kernel

Modifier and Type	Method and Description
void	KernelizedPassiveAggressiveClassification.setKernel(Kernel kernel)
void	BudgetedPassiveAggressiveClassification.setKernel(Kernel kernel)

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

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)

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

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

Modifier and Type	Method and Description
Kernel	KernelizedPerceptron.getKernel()

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

Modifier and Type	Method and Description
void	KernelizedPerceptron.setKernel(Kernel kernel)

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

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

Uses of Kernel in it.uniroma2.sag.kelp.learningalgorithm.clustering.kernelbasedkmeans

Methods in it.uniroma2.sag.kelp.learningalgorithm.clustering.kernelbasedkmeans that return Kernel

Modifier and Type	Method and Description
Kernel	KernelBasedKMeansEngine.getKernel()

Methods in it.uniroma2.sag.kelp.learningalgorithm.clustering.kernelbasedkmeans with parameters of type Kernel

Modifier and Type	Method and Description
void	KernelBasedKMeansEngine.setKernel(Kernel kernel)

Constructors in it.uniroma2.sag.kelp.learningalgorithm.clustering.kernelbasedkmeans with parameters of type Kernel

Constructor and Description
KernelBasedKMeansEngine(Kernel kernel, int k, int maxIterations)

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

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

Modifier and Type	Method and Description
void	EpsilonSvmRegression.setKernel(Kernel kernel)

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

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

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

Methods in it.uniroma2.sag.kelp.learningalgorithm.regression.passiveaggressive that return Kernel

Modifier and Type	Method and Description
Kernel	KernelizedPassiveAggressiveRegression.getKernel()

Methods in it.uniroma2.sag.kelp.learningalgorithm.regression.passiveaggressive with parameters of type Kernel

Modifier and Type	Method and Description
void	KernelizedPassiveAggressiveRegression.setKernel(Kernel kernel)

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

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

Uses of Kernel in it.uniroma2.sag.kelp.linearization.nystrom

Methods in it.uniroma2.sag.kelp.linearization.nystrom that return Kernel

Modifier and Type	Method and Description
Kernel	NystromMethod.getKernel()

Methods in it.uniroma2.sag.kelp.linearization.nystrom with parameters of type Kernel

Modifier and Type	Method and Description
void	NystromMethod.setKernel(Kernel kernel)

Constructors in it.uniroma2.sag.kelp.linearization.nystrom with parameters of type Kernel

Constructor and Description
NystromMethod(List<Example> landmarks, Kernel kernel) Constructor of NystromMethod.
NystromMethod(List<Example> landmarks, Kernel kernel, int expectedRank)
NystromMethodEnsemble(List<List<Example>> listOflandmarks, Kernel kernel)

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

Methods in it.uniroma2.sag.kelp.predictionfunction.model that return Kernel

Modifier and Type	Method and Description
Kernel	KernelMachineModel.getKernel()
Kernel	BinaryKernelMachineModel.getKernel()

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

Modifier and Type	Method and Description
void	KernelMachineModel.setKernel(Kernel kernel)
void	BinaryKernelMachineModel.setKernel(Kernel kernel)

Constructors in it.uniroma2.sag.kelp.predictionfunction.model with parameters of type Kernel

Constructor and Description
BinaryKernelMachineModel(Kernel kernel)