|
||||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
public class PMMMutualInformation
Class for the network structure of a
BayesianNetworkDiffSM
that is a permuted Markov model based on mutual information.
Nested Class Summary | |
---|---|
static class |
PMMMutualInformation.PMMMutualInformationParameterSet
Class for the parameters of a PMMMutualInformation structure
Measure . |
Nested classes/interfaces inherited from class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure |
---|
Measure.MeasureParameterSet |
Field Summary |
---|
Fields inherited from class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure |
---|
parameters |
Constructor Summary | |
---|---|
PMMMutualInformation(byte order,
BTMutualInformation.DataSource clazz,
double[] ess)
Creates a new PMMMutualInformation of order order . |
|
PMMMutualInformation(PMMMutualInformation.PMMMutualInformationParameterSet parameters)
Creates a new PMMMutualInformation from the corresponding
InstanceParameterSet parameters . |
|
PMMMutualInformation(StringBuffer buf)
The standard constructor for the interface Storable . |
Method Summary | |
---|---|
String |
getInstanceName()
Returns the name of the Measure and possibly some additional
information about the current instance. |
int[][] |
getParents(DataSet fg,
DataSet bg,
double[] weightsFg,
double[] weightsBg,
int length)
Returns the optimal parents for the given data and weights. |
String |
getXMLTag()
Returns the XML-tag for storing this measure |
Methods inherited from class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure |
---|
clone, fillTensor, fillTensor, getCMI, getCMI, getCurrentParameterSet, getEAR, getEAR, getMI, getMI, getStatistics, getStatisticsOrderTwo, isShiftable, sum, toParents, toXML, union |
Methods inherited from class java.lang.Object |
---|
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
---|
public PMMMutualInformation(byte order, BTMutualInformation.DataSource clazz, double[] ess) throws Exception
PMMMutualInformation
of order order
.
order
- the order, may be 1
or 2
.clazz
- the classes used for computation of mutual information, as
defined by BTMutualInformation.DataSource
ess
- the equivalent sample sizes of both classes
Exception
- if the order is not 1
or 2
public PMMMutualInformation(PMMMutualInformation.PMMMutualInformationParameterSet parameters) throws Exception
PMMMutualInformation
from the corresponding
InstanceParameterSet
parameters
.
parameters
- the corresponding parameters
Exception
- if the order is not 1
or 2
public PMMMutualInformation(StringBuffer buf) throws NonParsableException
Storable
.
Recreates a PMMMutualInformation
from its XML representation as
returned by Measure.toXML()
.
buf
- the XML representation as StringBuffer
NonParsableException
- if the XML code could not be parsedMethod Detail |
---|
public String getXMLTag()
Measure
getXMLTag
in class Measure
public String getInstanceName()
Measure
Measure
and possibly some additional
information about the current instance.
getInstanceName
in class Measure
Measure
public int[][] getParents(DataSet fg, DataSet bg, double[] weightsFg, double[] weightsBg, int length) throws Exception
Measure
p
at each position i
is build
as follows:
p[i][p.length - 1]
contains the index i
itselfp[i][p.length - 2]
contains the "most
important" parentp[i][0]
contains the "least important" parent
getParents
in class Measure
fg
- the data of the current (foreground) classbg
- the data of the negative (background) classweightsFg
- 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
p
with the optimal parents
Exception
- if the lengths do not match or other problems concerning the
data occur
|
||||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |