/*
* File: Kernel.java
* Authors: Justin Basilico
* Company: Sandia National Laboratories
* Project: Cognitive Foundry
*
* Copyright July 19, 2007, Sandia Corporation. Under the terms of Contract
* DE-AC04-94AL85000, there is a non-exclusive license for use of this work by
* or on behalf of the U.S. Government. Export of this program may require a
* license from the United States Government. See CopyrightHistory.txt for
* complete details.
*
*/
package gov.sandia.cognition.learning.function.kernel;
import gov.sandia.cognition.annotation.CodeReview;
import gov.sandia.cognition.util.CloneableSerializable;
/**
* The <code>Kernel</code> interface the functionality required from an object
* that implements a kernel function. A kernel is a function that takes two
* arguments and returns a double that is equivalent to the inner-product
* between two vectors in a high-dimensional space. That is, a kernel must
* satisfy Mercer's conditions and produce a matrix that is positive
* semi-definite. Typically the inner-product is not actually computed by
* creating the high-dimensional representation, but instead is computed quickly
* such that the result would be equivalent to operating in that
* high-dimensional space.
*
* It is recommended that a {@link Kernel} implement
* {@link CloneableSerializable}, though it is not required.
*
* @param <InputType> The type of the input to the Kernel. For example, Vector.
* @author Justin Basilico
* @since 2.0
*/
@CodeReview(
reviewer="Kevin R. Dixon",
date="2009-07-08",
changesNeeded=false,
comments="Looks fine."
)
public interface Kernel<InputType>
{
/**
* The role of a kernel is to evaluate some function that is equivalent to
* an inner product in some vector space. The kernel must satisfy Mercer's
* conditions in that the kernel matrix must be positive semi-definite.
*
* @param x The first item.
* @param y The second item.
* @return The kernel evaluated on the two given objects.
*/
public double evaluate(
InputType x,
InputType y);
}