com.rapidminer.operator.learner.functions.kernel.gaussianprocess
Class Model

java.lang.Object
  com.rapidminer.operator.learner.functions.kernel.gaussianprocess.Model

All Implemented Interfaces:

java.io.Serializable

public class Model
extends java.lang.Object
implements java.io.Serializable

The learned model.

Author:

Piotr Kasprzak, Ingo Mierswa

See Also:

Serialized Form

Constructor Summary

Model(Kernel kernel, double[][] basisVectors, Jama.Matrix alpha, Jama.Matrix C, Jama.Matrix Q, int d, boolean regression)
Constructors

Method Summary

double[]	apply(double[][] inputVectors) Apply the model to all input vectors
double	applyToVector(double[] x_new) Apply the model to a (new) input vector x_t+1 in order to get a prediction, which - as a GP-marignal at x_t+1 - is a one-dimensional gaussian distribution with mean m and covariance sigma^2 (2.22, the parameterisation lemma).
double[]	getBasisVector(int i)
double	getBasisVectorValue(int i, int j)
int	getInputDim()
int	getNumberOfBasisVectors()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Model

public Model(Kernel kernel,
             double[][] basisVectors,
             Jama.Matrix alpha,
             Jama.Matrix C,
             Jama.Matrix Q,
             int d,
             boolean regression)

Constructors

Method Detail

getNumberOfBasisVectors

public int getNumberOfBasisVectors()

getInputDim

public int getInputDim()

getBasisVector

public double[] getBasisVector(int i)

getBasisVectorValue

public double getBasisVectorValue(int i,
                                  int j)

applyToVector

public double applyToVector(double[] x_new)

Apply the model to a (new) input vector x_t+1 in order to get a prediction, which - as a GP-marignal at x_t+1 - is a one-dimensional gaussian distribution with mean m and covariance sigma^2 (2.22, the parameterisation lemma). Returns only the function value, the mapping to a classification must be done by the invoking method.

apply

public double[] apply(double[][] inputVectors)
               throws java.lang.Exception

Apply the model to all input vectors

Throws:

java.lang.Exception