Uses of Class
gov.sandia.cognition.learning.function.kernel.DefaultKernelContainer

Packages that use DefaultKernelContainer

Package	Description
gov.sandia.cognition.learning.algorithm.pca	Provides implementations of Principle Components Analysis (PCA).
gov.sandia.cognition.learning.function.kernel	Provides kernel functions.
gov.sandia.cognition.learning.function.scalar	Provides functions that output real numbers.
gov.sandia.cognition.statistics.bayesian	Provides algorithms for computing Bayesian estimates of parameters.

Uses of DefaultKernelContainer in gov.sandia.cognition.learning.algorithm.pca

Subclasses of DefaultKernelContainer in gov.sandia.cognition.learning.algorithm.pca

Modifier and Type	Class and Description
class	KernelPrincipalComponentsAnalysis<DataType> An implementation of the Kernel Principal Components Analysis (KPCA) algorithm.
static class	KernelPrincipalComponentsAnalysis.Function<DataType> The resulting transformation function learned by Kernel Principal Components Analysis.

Uses of DefaultKernelContainer in gov.sandia.cognition.learning.function.kernel

Subclasses of DefaultKernelContainer in gov.sandia.cognition.learning.function.kernel

Modifier and Type	Class and Description
class	ExponentialKernel<InputType> The ExponentialKernel class implements a kernel that applies the exponential function to the result of another kernel.
class	KernelDistanceMetric<InputType> The KernelDistanceMetric class implements a distance metric that utilizes an underlying Kernel for computing the distance.
class	NormalizedKernel<InputType> The NormalizedKernel class implements an Kernel that returns a normalized value between 0.0 and 1.0 by normalizing the results of a given kernel.
class	VectorFunctionKernel The VectorFunctionKernel implements a kernel that makes use of a vector function plus a kernel that operates on vectors.
class	WeightedKernel<InputType> The WeightedKernel class implements a kernel that takes another kernel, evaluates it, and then the result is rescaled by a given weight.

Methods in gov.sandia.cognition.learning.function.kernel that return DefaultKernelContainer

Modifier and Type	Method and Description
DefaultKernelContainer<InputType>	DefaultKernelContainer.clone()

Constructors in gov.sandia.cognition.learning.function.kernel with parameters of type DefaultKernelContainer

Constructor and Description
DefaultKernelContainer(DefaultKernelContainer<? super InputType> other) Creates a new copy of a KernelContainer and the kernel inside.

Uses of DefaultKernelContainer in gov.sandia.cognition.learning.function.scalar

Subclasses of DefaultKernelContainer in gov.sandia.cognition.learning.function.scalar

Modifier and Type	Class and Description
class	KernelScalarFunction<InputType> The KernelScalarFunction class implements a scalar function that uses a kernel to compute its output value.
class	LocallyWeightedKernelScalarFunction<InputType> The LocallyWeightedKernelScalarFunction class implements a scalar function that uses kernels and does local weighting on them to get the result value.

Uses of DefaultKernelContainer in gov.sandia.cognition.statistics.bayesian

Subclasses of DefaultKernelContainer in gov.sandia.cognition.statistics.bayesian

Modifier and Type	Class and Description
class	GaussianProcessRegression<InputType> Gaussian Process Regression, is also known as Kriging, is a nonparametric method to interpolate and extrapolate using Bayesian regression, where the expressiveness of the estimator can grow with the data.