Uses of Class
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.HMMTrainingParameterSet

Packages that use HMMTrainingParameterSet
de.jstacs.sequenceScores.statisticalModels.trainable.hmm The package provides all interfaces and classes for a hidden Markov model (HMM). 
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models The package provides different implementations of hidden Markov models based on AbstractHMM
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training The package provides all classes used to determine the training algorithm of a hidden Markov model. 
 

Uses of HMMTrainingParameterSet in de.jstacs.sequenceScores.statisticalModels.trainable.hmm
 

Fields in de.jstacs.sequenceScores.statisticalModels.trainable.hmm declared as HMMTrainingParameterSet
protected  HMMTrainingParameterSet AbstractHMM.trainingParameter
          The ParameterSet containing all Parameters for the training of the HMM.
 

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm with parameters of type HMMTrainingParameterSet
static AbstractHMM HMMFactory.createErgodicHMM(HMMTrainingParameterSet pars, int order, double ess, double selfTranistionPart, double expectedSequenceLength, Emission... emission)
          This method creates an ergodic, i.e.
static AbstractHMM HMMFactory.createPseudoErgodicHMM(HMMTrainingParameterSet pars, double ess, double selfTranistionPart, double finalTranistionPart, AlphabetContainer con, int numStates, boolean insertUniform)
          Creates an HMM with numStates+1 states, where numStates emitting build a clique and each of those states is connected to the absorbing silent final state.
static AbstractHMM HMMFactory.createSunflowerHMM(HMMTrainingParameterSet pars, AlphabetContainer con, double ess, int expectedSequenceLength, boolean startCentral, int... motifLength)
          This method creates a first order sunflower HMM.
static AbstractHMM HMMFactory.createSunflowerHMM(HMMTrainingParameterSet pars, AlphabetContainer con, double ess, int expectedSequenceLength, boolean startCentral, PhyloTree[] t, double[] motifProb, int[] motifLength)
          This method creates a first order sunflower HMM allowing phylogenetic emissions.
 

Constructors in de.jstacs.sequenceScores.statisticalModels.trainable.hmm with parameters of type HMMTrainingParameterSet
AbstractHMM(HMMTrainingParameterSet trainingParameterSet, String[] name, int[] emissionIdx, boolean[] forward, Emission[] emission)
          This is the main constructor for an HMM.
 

Uses of HMMTrainingParameterSet in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models
 

Constructors in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models with parameters of type HMMTrainingParameterSet
HigherOrderHMM(HMMTrainingParameterSet trainingParameterSet, String[] name, Emission[] emission, BasicHigherOrderTransition.AbstractTransitionElement... te)
          This is a convenience constructor.
HigherOrderHMM(HMMTrainingParameterSet trainingParameterSet, String[] name, int[] emissionIdx, boolean[] forward, Emission[] emission, BasicHigherOrderTransition.AbstractTransitionElement... te)
          This is the main constructor.
 

Uses of HMMTrainingParameterSet in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training
 

Subclasses of HMMTrainingParameterSet in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training
 class BaumWelchParameterSet
          This class implements an HMMTrainingParameterSet for the Baum-Welch training of an AbstractHMM.
 class MaxHMMTrainingParameterSet
          This class is the super class for any HMMTrainingParameterSet that is used for a maximizing training algorithm of a hidden Markov model.
 class MultiThreadedTrainingParameterSet
          This class is the super class for any MaxHMMTrainingParameterSet that is used for a multi-threaded maximizing training algorithm of a hidden Markov model.
 class NumericalHMMTrainingParameterSet
          This class implements an ParameterSet for numerical training of an AbstractHMM.
 class SamplingHMMTrainingParameterSet
          This class contains the parameters for training training an AbstractHMM using a sampling strategy.
 class ViterbiParameterSet
          This class implements an ParameterSet for the viterbi training of an AbstractHMM.