de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous
Class FSMEManager
java.lang.Object
de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhomogeneousDGTrainSM
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSMEManager
- All Implemented Interfaces:
- InstantiableFromParameterSet, SequenceScore, StatisticalModel, TrainableStatisticalModel, Storable, Cloneable
public class FSMEManager
- extends MEManager
This class can be used for any discrete fixed structure maximum entropy model (FSMEM).
- Author:
- Jens Keilwagen
Fields inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager |
factors |
Methods inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager |
clone, emitDataSet, getFactors, getFactors, getFurtherModelInfos, getLogPriorTerm, getLogProbFor, getNumericalCharacteristics, getStructure, setFurtherModelInfos, toString, trainFactors |
Methods inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel |
getAlphabetContainer, getCharacteristics, getLength, getLogProbFor, getLogProbFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, getMaximalMarkovOrder, toString, train |
FSMEManager
public FSMEManager(FSMEMParameterSet params)
throws CloneNotSupportedException,
IllegalArgumentException,
NonParsableException
- Creates a new
MEManager
from a given
MEManagerParameterSet
.
- Parameters:
params
- the given parameter set
- Throws:
CloneNotSupportedException
- if the parameter set could not be cloned
IllegalArgumentException
- if the parameter set is not instantiated
NonParsableException
- if the parameter set is not parsable- See Also:
MEManager.MEManager(MEManagerParameterSet)
FSMEManager
public FSMEManager(StringBuffer stringBuff)
throws NonParsableException
- The standard constructor for the interface
Storable
.
Creates a new FSMEManager
out of its XML representation.
- Parameters:
stringBuff
- the XML representation as StringBuffer
- Throws:
NonParsableException
- if the FSMEManager
could not be reconstructed
out of the XML representation (the StringBuffer
could
not be parsed)- See Also:
Storable
,
MEManager.MEManager(StringBuffer)
getInstanceName
public String getInstanceName()
- Description copied from interface:
SequenceScore
- Should return a short instance name such as iMM(0), BN(2), ...
- Returns:
- a short instance name
train
public void train(DataSet data,
double[] weights)
throws Exception
- Description copied from interface:
TrainableStatisticalModel
- Trains the
TrainableStatisticalModel
object given the data as DataSet
using
the specified weights. The weight at position i belongs to the element at
position i. So the array weight
should have the number of
sequences in the data set as dimension. (Optionally it is possible to use
weight == null
if all weights have the value one.)
This method should work non-incrementally. That means the result of the
following series: train(data1)
; train(data2)
should be a fully trained model over data2
and not over
data1+data2
. All parameters of the model were given by the
call of the constructor.
- Parameters:
data
- the given sequences as DataSet
weights
- the weights of the elements, each weight should be
non-negative
- Throws:
Exception
- if the training did not succeed (e.g. the dimension of
weights
and the number of sequences in the
data set do not match)- See Also:
DataSet.getElementAt(int)
,
DataSet.ElementEnumerator
getXMLTag
protected String getXMLTag()
- Description copied from class:
DiscreteGraphicalTrainSM
- Returns the XML tag that is used for this model in
DiscreteGraphicalTrainSM.fromXML(StringBuffer)
and DiscreteGraphicalTrainSM.toXML()
.
- Specified by:
getXMLTag
in class DiscreteGraphicalTrainSM
- Returns:
- the XML tag that is used in
DiscreteGraphicalTrainSM.fromXML(StringBuffer)
and
DiscreteGraphicalTrainSM.toXML()
- See Also:
DiscreteGraphicalTrainSM.fromXML(StringBuffer)
,
DiscreteGraphicalTrainSM.toXML()
set
protected void set(DGTrainSMParameterSet params,
boolean trained)
throws CloneNotSupportedException,
NonParsableException
- Description copied from class:
DiscreteGraphicalTrainSM
- Sets the parameters as internal parameters and does some essential
computations. Used in
fromParameterSet
-methods.
- Overrides:
set
in class InhomogeneousDGTrainSM
- Parameters:
params
- the new ParameterSet
trained
- indicates if the model is trained or not
- Throws:
CloneNotSupportedException
- if the parameter set could not be cloned
NonParsableException
- if the parameters of the model could not be parsed