Environment for
DeveLoping
KDD-Applications
Supported by Index-Structures

Package de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel

Kernel functions.

See:
          Description

Interface Summary
KernelFunction<O extends DatabaseObject,D extends Distance<D>> Interface Kernel describes the requirements of any kernel function.
 

Class Summary
AbstractDoubleKernelFunction<O extends DatabaseObject> Provides an abstract superclass for KernelFunctions that are based on DoubleDistance.
AbstractKernelFunction<O extends DatabaseObject,D extends Distance<D>> AbstractKernelFunction provides some methods valid for any extending class.
ArbitraryKernelFunctionWrapper<O extends RealVector<O,?>> Provides a wrapper for arbitrary kernel functions whose kernel matrix has been precomputed.
FooKernelFunction<O extends FeatureVector<?,?>> Provides an experimental KernelDistanceFunction for RealVectors.
KernelMatrix<O extends RealVector<O,?>> Provides a class for storing the kernel matrix and several extraction methods for convenience.
LinearKernelFunction<O extends FeatureVector<O,?>> Provides a linear Kernel function that computes a similarity between the two feature vectors V1 and V2 defined by V1^T*V2.
PolynomialKernelFunction<O extends FeatureVector<O,?>> Provides a polynomial Kernel function that computes a similarity between the two feature vectors V1 and V2 defined by (V1^T*V2)^degree.
 

Package de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel Description

Kernel functions.


Release 0.2 (2009-07-06_1820)