de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures
Class InhomogeneousMarkov

java.lang.Object
  de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
      de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov

All Implemented Interfaces:

InstantiableFromParameterSet, Storable, Cloneable

public class InhomogeneousMarkov
extends Measure

Class for a network structure of a BayesianNetworkScoringFunction that is an inhomogeneous Markov model. The order of the Markov model can be defined by the user. A Markov model of order 0 is also know as position weight matrix (PWM), a Markov model of order 1 is also known as weight array matrix (WAM) model.

Author:

Jan Grau

Nested Class Summary

static class

InhomogeneousMarkov.InhomogeneousMarkovParameterSet Class for an InstanceParameterSet that defines the parameters of a InhomogeneousMarkov structure Measure.

Constructor Summary

InhomogeneousMarkov(InhomogeneousMarkov.InhomogeneousMarkovParameterSet parameters)
Creates a new InhomogeneousMarkov from the corresponding InstanceParameterSet parameters.

InhomogeneousMarkov(int order)
Creates the structure of an inhomogeneous Markov model of order order.

InhomogeneousMarkov(StringBuffer buf)
Re-creates an InhomogeneousMarkov structure from its XML-representation as returned by toXML().

Method Summary

InhomogeneousMarkov	clone()
InstanceParameterSet	getCurrentParameterSet() Returns the InstanceParameterSet that has been used to instantiate the current instance of the implementing class.
String	getInstanceName() Returns the name of the Measure and possibly some additional information about the current instance.
int	getOrder() Returns the order of the Markov model as defined in the constructor
int[][]	getParents(Sample fg, Sample bg, double[] weightsFg, double[] weightsBg, int length) Returns the optimal parents for the given data and weights.
boolean	isShiftable() Indicates if Measure supports shifts.
StringBuffer	toXML() This method returns an XML-representation of an instance of the implementing class.

Methods inherited from class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure

fillTensor, fillTensor, getCMI, getCMI, getEAR, getEAR, getMI, getMI, getStatistics, getStatisticsOrderTwo, sum, toParents, union

Methods inherited from class java.lang.Object

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

Constructor Detail

InhomogeneousMarkov

public InhomogeneousMarkov(int order)

Creates the structure of an inhomogeneous Markov model of order order.

Parameters:

order - the order

InhomogeneousMarkov

public InhomogeneousMarkov(InhomogeneousMarkov.InhomogeneousMarkovParameterSet parameters)

Creates a new InhomogeneousMarkov from the corresponding InstanceParameterSet parameters.

Parameters:

parameters - the parameters

InhomogeneousMarkov

public InhomogeneousMarkov(StringBuffer buf)
                    throws NonParsableException

Re-creates an InhomogeneousMarkov structure from its XML-representation as returned by toXML().

Parameters:

buf - the XML-representation

Throws:

NonParsableException - is thrown if the XML-code could not be parsed

Method Detail

getOrder

public int getOrder()

Returns the order of the Markov model as defined in the constructor

Returns:

the order

clone

public InhomogeneousMarkov clone()
                          throws CloneNotSupportedException

Overrides:

clone in class Measure

Throws:

CloneNotSupportedException

getInstanceName

public String getInstanceName()

Description copied from class: Measure

Returns the name of the Measure and possibly some additional information about the current instance.

Specified by:

getInstanceName in class Measure

Returns:

the name

getParents

public int[][] getParents(Sample fg,
                          Sample bg,
                          double[] weightsFg,
                          double[] weightsBg,
                          int length)
                   throws Exception

Description copied from class: Measure

Returns the optimal parents for the given data and weights. The array of parents p at each position i is build as follows:

• p[i][p.length - 1] contains the index i itself
• p[i][p.length - 2] contains the "most important" parent
• ...
• p[i][0] contains the "least important parent

Specified by:

getParents in class Measure

Parameters:

fg - the data of the current (foreground) class

bg - the data of the negative (background) class

weightsFg - the weights for the sequences of fg

weightsBg - the weights for the sequences of bg

length - the length of the model, must be equal to the length of the sequences

Returns:

the parents

Throws:

Exception - thrown if the lengths do not match or other problems concerning the data occur

isShiftable

public boolean isShiftable()

Description copied from class: Measure

Indicates if Measure supports shifts.

Overrides:

isShiftable in class Measure

Returns:

if Measure supports shifts

toXML

public StringBuffer toXML()

Description copied from interface: Storable

This method returns an XML-representation of an instance of the implementing class.

Returns:

the XML-representation

getCurrentParameterSet

public InstanceParameterSet getCurrentParameterSet()
                                            throws Exception

Description copied from interface: InstantiableFromParameterSet

Returns the InstanceParameterSet that has been used to instantiate the current instance of the implementing class. If the current instance was not created using a InstanceParameterSet, an equivalent InstanceParameterSet should be returned, such that an instance created using this InstanceParameterSet would be in principle equal to the current instance.

Returns:

the current InstanceParameterSet

Throws:

Exception - is thrown if the InstanceParameterSet could not be returned