Uses of Package
jsat.distributions.kernels

Packages that use jsat.distributions.kernels

Package	Description
jsat.classifiers.linear.kernelized
jsat.classifiers.svm
jsat.clustering.kmeans
jsat.datatransform.kernel
jsat.distributions.kernels
jsat.linear.distancemetrics
jsat.regression

Classes in jsat.distributions.kernels used by jsat.classifiers.linear.kernelized

Class and Description
KernelPoint.BudgetStrategy These enums control the method used to reduce the size of the support vector set in the kernel point.
KernelTrick The KernelTrick is a method can can be used to alter an algorithm to do its calculations in a projected feature space, without explicitly forming the features.

Classes in jsat.distributions.kernels used by jsat.classifiers.svm

Class and Description
KernelTrick The KernelTrick is a method can can be used to alter an algorithm to do its calculations in a projected feature space, without explicitly forming the features.

Classes in jsat.distributions.kernels used by jsat.clustering.kmeans

Class and Description
KernelTrick The KernelTrick is a method can can be used to alter an algorithm to do its calculations in a projected feature space, without explicitly forming the features.

Classes in jsat.distributions.kernels used by jsat.datatransform.kernel

Class and Description
KernelTrick The KernelTrick is a method can can be used to alter an algorithm to do its calculations in a projected feature space, without explicitly forming the features.

Classes in jsat.distributions.kernels used by jsat.distributions.kernels

Class and Description
BaseKernelTrick This provides a simple base implementation for the cache related methods in Kernel Trick.
BaseL2Kernel Many Kernels can be described in terms the L2 norm with some operations performed on it.
DistanceMetricBasedKernel This abstract class provides the means of implementing a Kernel based off some DistanceMetric.
KernelPoint The Kernel Point represents a kernelized weight vector by a linear combination of vectors transformed through a kernel fuctiion.
KernelPoint.BudgetStrategy These enums control the method used to reduce the size of the support vector set in the kernel point.
KernelPoints This class represents a list of KernelPoint objects.
KernelTrick The KernelTrick is a method can can be used to alter an algorithm to do its calculations in a projected feature space, without explicitly forming the features.
LinearKernel Provides a linear kernel function, which computes the normal dot product.
NormalizedKernel This provides a wrapper kernel that produces a normalized kernel trick from any input kernel trick.
PolynomialKernel Provides a Polynomial Kernel of the form k(x,y) = (alpha * x.y + c)^d
PukKernel The PUK kernel is an alternative to the RBF Kernel.
RationalQuadraticKernel Provides an implementation of the Rational Quadratic Kernel, which is of the form: k(x, y) = 1 - ||x-y||2 / (||x-y||2 + c)
RBFKernel Provides a kernel for the Radial Basis Function, which is of the form k(x, y) = exp(-||x-y||2/(2*σ2))
SigmoidKernel Provides an implementation of the Sigmoid (Hyperbolic Tangent) Kernel, which is of the form: k(x, y) = tanh(alpha * < x, y > +c) Technically, this kernel is not positive definite.

Classes in jsat.distributions.kernels used by jsat.linear.distancemetrics

Class and Description
KernelTrick The KernelTrick is a method can can be used to alter an algorithm to do its calculations in a projected feature space, without explicitly forming the features.

Classes in jsat.distributions.kernels used by jsat.regression

Class and Description
KernelTrick The KernelTrick is a method can can be used to alter an algorithm to do its calculations in a projected feature space, without explicitly forming the features.