| Modifier and Type | Class and Description | 
|---|---|
| class  | DirectKernel<T extends Representation>It is a kernel that operates exploiting directly on a specific
 representation. | 
| class  | KernelCombinationIt is a kernel that operates combining other kernels | 
| class  | KernelCompositionIt is a kernel that operates enriching the computation performed by another kernel | 
| Modifier and Type | Field and Description | 
|---|---|
| protected Kernel | KernelComposition. baseKernel | 
| Modifier and Type | Field and Description | 
|---|---|
| protected List<Kernel> | KernelCombination. toCombine | 
| Modifier and Type | Method and Description | 
|---|---|
| Kernel | KernelComposition. getBaseKernel()Returns the kernel this kernel is enriching | 
| Modifier and Type | Method and Description | 
|---|---|
| List<Kernel> | KernelCombination. getToCombine()Returns a list of the kernels this kernel is combining | 
| Modifier and Type | Method and Description | 
|---|---|
| void | KernelComposition. setBaseKernel(Kernel baseKernel) | 
| Modifier and Type | Method and Description | 
|---|---|
| void | KernelCombination. setToCombine(List<Kernel> toCombine) | 
| Modifier and Type | Class and Description | 
|---|---|
| class  | PreferenceKernelIt is a kernel operating of ExamplePairs applying the following formula: \(K( < x_1, x_2 >, < y_1,y_2 > ) = K(x_1, y_1) + K(x_2, y_2) - K(x_1, y_2) - K(x_2, y_1)\) where K is another kernel the preference kernel relies on. | 
| Constructor and Description | 
|---|
| PreferenceKernel(Kernel baseKernel) | 
| Modifier and Type | Class and Description | 
|---|---|
| class  | LinearKernelCombinationWeighted Linear Combination of Kernels
  Given a kernel some kernel K1...Km, with weights c1,...cn, the combination formula is: SUM(Ki*ci) | 
| class  | NormalizationKernelNormalization 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  | RbfKernelRadial Basis Function 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 | 
| 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) | 
| Modifier and Type | Class and Description | 
|---|---|
| class  | PartialTreeKernelPartial Tree Kernel implementation. | 
| class  | SubTreeKernelSubTree Kernel implementation. | 
| Modifier and Type | Class and Description | 
|---|---|
| class  | LinearKernelLinear Kernel for  VectorsIt executes the dot product between two Vectorrepresentations | 
| Modifier and Type | Method and Description | 
|---|---|
| Kernel | KernelMethod. getKernel()Returns the kernel exploited by this learner | 
| Modifier and Type | Method and Description | 
|---|---|
| void | KernelMethod. setKernel(Kernel kernel)Sets the kernel this | 
| Modifier and Type | Method and Description | 
|---|---|
| void | BinaryNuSvmClassification. setKernel(Kernel kernel) | 
| void | BinaryCSvmClassification. setKernel(Kernel 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) | 
| Modifier and Type | Field and Description | 
|---|---|
| protected Kernel | LibSvmSolver. kernelThe Kernel function between examples, i.e. | 
| Modifier and Type | Method and Description | 
|---|---|
| Kernel | LibSvmSolver. getKernel() | 
| Constructor and Description | 
|---|
| LibCSvmSolver(Kernel kernel,
             float cp,
             float cn) | 
| LibNuSvmSolver(Kernel kernel,
              int cp,
              int cn) | 
| LibSvmSolver(Kernel kernel,
            float Cp,
            float Cn) | 
| Modifier and Type | Method and Description | 
|---|---|
| Kernel | KernelizedPassiveAggressiveClassification. getKernel() | 
| Modifier and Type | Method and Description | 
|---|---|
| void | KernelizedPassiveAggressiveClassification. setKernel(Kernel kernel) | 
| Constructor and Description | 
|---|
| KernelizedPassiveAggressiveClassification(float cp,
                                         float cn,
                                         PassiveAggressiveClassification.Loss loss,
                                         Kernel kernel,
                                         Label label) | 
| Modifier and Type | Method and Description | 
|---|---|
| Kernel | KernelizedPerceptron. getKernel() | 
| Modifier and Type | Method and Description | 
|---|---|
| void | KernelizedPerceptron. setKernel(Kernel kernel) | 
| Constructor and Description | 
|---|
| KernelizedPerceptron(float alpha,
                    float margin,
                    boolean unbiased,
                    Kernel kernel,
                    Label label) | 
| Modifier and Type | Method and Description | 
|---|---|
| Kernel | KernelBasedKMeansEngine. getKernel() | 
| Modifier and Type | Method and Description | 
|---|---|
| void | KernelBasedKMeansEngine. setKernel(Kernel kernel) | 
| Constructor and Description | 
|---|
| KernelBasedKMeansEngine(Kernel kernel,
                       int k,
                       int maxIterations) | 
| Modifier and Type | Method and Description | 
|---|---|
| void | EpsilonSvmRegression. setKernel(Kernel kernel) | 
| Constructor and Description | 
|---|
| EpsilonSvmRegression(Kernel kernel,
                    Label label,
                    float c,
                    float pReg) | 
| Modifier and Type | Method and Description | 
|---|---|
| Kernel | KernelizedPassiveAggressiveRegression. getKernel() | 
| Modifier and Type | Method and Description | 
|---|---|
| void | KernelizedPassiveAggressiveRegression. setKernel(Kernel kernel) | 
| Constructor and Description | 
|---|
| KernelizedPassiveAggressiveRegression(float aggressiveness,
                                     float epsilon,
                                     PassiveAggressive.Policy policy,
                                     Kernel kernel,
                                     Label label) | 
| Modifier and Type | Method and Description | 
|---|---|
| Kernel | KernelMachineModel. getKernel() | 
| Kernel | BinaryKernelMachineModel. getKernel() | 
| Modifier and Type | Method and Description | 
|---|---|
| void | KernelMachineModel. setKernel(Kernel kernel) | 
| void | BinaryKernelMachineModel. setKernel(Kernel kernel) | 
| Constructor and Description | 
|---|
| BinaryKernelMachineModel(Kernel kernel) | 
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