public class InhomogeneousPMM extends AbstractParsimoniousModel implements de.jstacs.InstantiableFromParameterSet
Modifier and Type | Field and Description |
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protected static java.lang.String |
XML_TAG |
inSamplingMode, learningMethod, parameterSamples, trained, tree, usedModelType, usedParameterEstimate, usedStructureScore
numberOfSamples, reader, sampleFilePath, writer
Constructor and Description |
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InhomogeneousPMM(InhPMMParameterSet params)
Constructs an inhomogeneous parsimonious Markov model (PMM) from a
|
InhomogeneousPMM(java.lang.StringBuffer sb)
The standard constructor for the interface
Storable . |
Modifier and Type | Method and Description |
---|---|
InhomogeneousPMM |
clone() |
void |
drawParameters(de.jstacs.data.DataSet data) |
protected void |
fromXML(java.lang.StringBuffer xml) |
de.jstacs.parameters.InstanceParameterSet<? extends de.jstacs.InstantiableFromParameterSet> |
getCurrentParameterSet() |
double |
getESS() |
java.lang.String |
getInstanceName() |
double |
getLogPriorTerm() |
double |
getLogProbFor(de.jstacs.data.sequences.Sequence seq,
int start,
int end) |
double |
getLogScoreOfCurrentStructure()
The function returns the score (AIC, BIC, NML, Bayes) of the currently selected structure.
|
int |
getNumberOfLeaves() |
de.jstacs.results.NumericalResultSet |
getNumericalCharacteristics() |
byte |
getOrder() |
java.lang.String |
getXMLTag() |
boolean |
isTrained() |
void |
setSampleFilePath(java.lang.String s) |
java.lang.String |
toString(java.text.NumberFormat nf) |
java.lang.StringBuffer |
toXML() |
void |
train(de.jstacs.data.DataSet data,
double[] weights) |
void |
train(de.jstacs.data.DataSet data,
double[] weights,
ParsimoniousElement.StructureScore structureScore,
ParsimoniousElement.ParameterEstimate parameterEstimate) |
void |
train(de.jstacs.data.DataSet data,
ParsimoniousElement.StructureScore structureScore,
ParsimoniousElement.ParameterEstimate parameterEstimate) |
getGraphViz, getLearningMethod, getSparseParameterRepresentation, getTreeStructures, initForSampling, isInitialized, parse, samplingStopped, saveCurrentParametersToFile, setModelType, setParameterEstimate, setStructureScore
check, emitDataSet, getAlphabetContainer, getCharacteristics, getLength, getLogProbFor, getLogProbFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, getMaximalMarkovOrder, toString, train
protected static final java.lang.String XML_TAG
public InhomogeneousPMM(InhPMMParameterSet params) throws java.lang.Exception
params
- given parameter set.java.lang.Exception
public InhomogeneousPMM(java.lang.StringBuffer sb) throws de.jstacs.io.NonParsableException
Storable
.
Creates a new InhomogeneousPMM
out of a StringBuffer
.sb
- the StringBuffer
to be parsedde.jstacs.io.NonParsableException
- is thrown if the StringBuffer
could not be parsedprotected void fromXML(java.lang.StringBuffer xml) throws de.jstacs.io.NonParsableException
fromXML
in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
de.jstacs.io.NonParsableException
public void drawParameters(de.jstacs.data.DataSet data) throws java.lang.Exception
drawParameters
in class AbstractVariableStructureModel
java.lang.Exception
public java.lang.StringBuffer toXML()
toXML
in interface de.jstacs.Storable
public java.lang.String getInstanceName()
getInstanceName
in interface de.jstacs.sequenceScores.SequenceScore
public double getLogPriorTerm() throws java.lang.Exception
getLogPriorTerm
in interface de.jstacs.sequenceScores.statisticalModels.StatisticalModel
java.lang.Exception
public de.jstacs.results.NumericalResultSet getNumericalCharacteristics() throws java.lang.Exception
getNumericalCharacteristics
in interface de.jstacs.sequenceScores.SequenceScore
java.lang.Exception
public double getLogProbFor(de.jstacs.data.sequences.Sequence seq, int start, int end) throws java.lang.Exception
getLogProbFor
in interface de.jstacs.sequenceScores.statisticalModels.StatisticalModel
java.lang.Exception
public boolean isTrained()
public java.lang.String getXMLTag()
public InhomogeneousPMM clone() throws java.lang.CloneNotSupportedException
clone
in interface de.jstacs.sequenceScores.SequenceScore
clone
in interface de.jstacs.sequenceScores.statisticalModels.trainable.TrainableStatisticalModel
clone
in class AbstractVariableStructureModel
java.lang.CloneNotSupportedException
public int getNumberOfLeaves()
public void train(de.jstacs.data.DataSet data, double[] weights) throws java.lang.Exception
train
in interface de.jstacs.sequenceScores.statisticalModels.trainable.TrainableStatisticalModel
java.lang.Exception
public void train(de.jstacs.data.DataSet data, double[] weights, ParsimoniousElement.StructureScore structureScore, ParsimoniousElement.ParameterEstimate parameterEstimate) throws java.lang.Exception
java.lang.Exception
public void train(de.jstacs.data.DataSet data, ParsimoniousElement.StructureScore structureScore, ParsimoniousElement.ParameterEstimate parameterEstimate) throws java.lang.Exception
java.lang.Exception
public byte getOrder()
public double getESS()
public double getLogScoreOfCurrentStructure()
AbstractVariableStructureModel
getLogScoreOfCurrentStructure
in class AbstractVariableStructureModel
public java.lang.String toString(java.text.NumberFormat nf)
toString
in interface de.jstacs.sequenceScores.SequenceScore
public de.jstacs.parameters.InstanceParameterSet<? extends de.jstacs.InstantiableFromParameterSet> getCurrentParameterSet() throws java.lang.Exception
getCurrentParameterSet
in interface de.jstacs.InstantiableFromParameterSet
java.lang.Exception
public void setSampleFilePath(java.lang.String s)