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. a completely connected, HMM using the given emissions.
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.