public abstract class HomogeneousDiffSM extends AbstractVariableLengthDiffSM implements SamplingDifferentiableStatisticalModel
DifferentiableSequenceScore
s.alphabets, length, r
UNKNOWN
Modifier | Constructor and Description |
---|---|
protected |
HomogeneousDiffSM(AlphabetContainer alphabets)
This is the main constructor that creates an instance of a
HomogeneousDiffSM that models sequences of arbitrary
length. |
protected |
HomogeneousDiffSM(AlphabetContainer alphabets,
int length)
This is the main constructor that creates an instance of a
HomogeneousDiffSM that models sequences of a given
length. |
protected |
HomogeneousDiffSM(StringBuffer source)
This is the constructor for
Storable . |
Modifier and Type | Method and Description |
---|---|
abstract byte |
getMaximalMarkovOrder()
Returns the maximal used markov oder.
|
abstract void |
initializeUniformly(boolean freeParams)
This method allows to initialize the instance with an uniform distribution.
|
getLogNormalizationConstant, getLogPartialNormalizationConstant, getLogScoreAndPartialDerivation, getLogScoreAndPartialDerivation, getLogScoreFor, getLogScoreFor
clone, emitDataSet, getInitialClassParam, getLogProbFor, getLogProbFor, getLogProbFor, getLogScoreFor, getLogScoreFor, isNormalized, isNormalized
fromXML, getAlphabetContainer, getCharacteristics, getLength, getLogScoreAndPartialDerivation, getLogScoreFor, getNumberOfRecommendedStarts, getNumberOfStarts, getNumericalCharacteristics, toString
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
getSamplingGroups
addGradientOfLogPriorTerm, getESS, getLogNormalizationConstant, getLogPartialNormalizationConstant, getLogPriorTerm, getSizeOfEventSpaceForRandomVariablesOfParameter, isNormalized
clone, getCurrentParameterValues, getInitialClassParam, getLogScoreAndPartialDerivation, getLogScoreAndPartialDerivation, getLogScoreAndPartialDerivation, getNumberOfParameters, getNumberOfRecommendedStarts, initializeFunction, initializeFunctionRandomly, setParameters
emitDataSet, getLogProbFor, getLogProbFor, getLogProbFor
getAlphabetContainer, getCharacteristics, getInstanceName, getLength, getLogScoreFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, getNumericalCharacteristics, isInitialized, toString
getLogNormalizationConstant, getLogPartialNormalizationConstant, setStatisticForHyperparameters
protected HomogeneousDiffSM(AlphabetContainer alphabets)
HomogeneousDiffSM
that models sequences of arbitrary
length.alphabets
- the AlphabetContainer
protected HomogeneousDiffSM(AlphabetContainer alphabets, int length)
HomogeneousDiffSM
that models sequences of a given
length.alphabets
- the AlphabetContainer
length
- the length of the modeled sequencesprotected HomogeneousDiffSM(StringBuffer source) throws NonParsableException
Storable
. Creates a new
HomogeneousDiffSM
out of its XML representation.source
- the XML representation as StringBuffer
NonParsableException
- if the XML representation could not be parsedpublic abstract byte getMaximalMarkovOrder()
getMaximalMarkovOrder
in interface StatisticalModel
getMaximalMarkovOrder
in class AbstractDifferentiableStatisticalModel
public abstract void initializeUniformly(boolean freeParams)
freeParams
- a switch whether to take only free parameters or to take all