Uses of Interface
calhoun.analysis.crf.ModelManager

Packages that use ModelManager

calhoun.analysis.crf	the interface, main Conrad class, and solver for the Conrad engine.
calhoun.analysis.crf.features.generic	features useful across different models
calhoun.analysis.crf.features.interval13	mdoel definition and setup for the interval13 model
calhoun.analysis.crf.features.interval29
calhoun.analysis.crf.features.supporting.phylogenetic	utility classes for phylogenetic analysis
calhoun.analysis.crf.features.tricycle13	basic features and model for the tricycle13 gene calling model
calhoun.analysis.crf.io	handles input and output of gene calling formats
calhoun.analysis.crf.solver	training and inference algorithms used in the CRF engine
calhoun.analysis.crf.solver.semimarkov
calhoun.analysis.crf.test

Uses of ModelManager in calhoun.analysis.crf

Classes in calhoun.analysis.crf that implement ModelManager

class

BeanModel a useful base class for creating model beans.

Methods in calhoun.analysis.crf that return ModelManager

ModelManager

Conrad.getModel() returns the configured ModelManager object.

Methods in calhoun.analysis.crf with parameters of type ModelManager

double[]	CRFTraining.optimize(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data) find the set of weights which maximizes the value of the objective function.
CRFInference.InferenceResult	CRFInference.predict(ModelManager mm, InputSequence<?> data, double[] weights) Return the labelling that maximizes the conditional probability P(y|x).
void	Conrad.setModel(ModelManager model) sets the model.
void	CRFObjectiveFunctionGradient.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data) sets the training data that will be used for evaluation of the objective function.
void	ConstrainedFeatureManager.train(int startingIndex, ModelManager modelInfo, java.util.List data)
void	CompositeFeatureManager.train(int startingIndex, ModelManager modelInfo, java.util.List data)
void	FeatureManager.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends InputType>> data) Provides access to the entire training set so that FeatureManager can compute global properties and assign feature indices.

Uses of ModelManager in calhoun.analysis.crf.features.generic

Methods in calhoun.analysis.crf.features.generic with parameters of type ModelManager

void	StartFeatures.train(int startingIndex, ModelManager modelInfo, java.util.List data) Start features don't train based on the data.
void	IndicatorEdges.train(int startingIndex, ModelManager modelInfo, java.util.List data) Edge features don't train based on the data.
void	EndFeatures.train(int startingIndex, ModelManager modelInfo, java.util.List data) Edge features don't train based on the data.
void	WeightedStateChanges.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<?>> data)
void	WeightedEdges.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<?>> data)

Uses of ModelManager in calhoun.analysis.crf.features.interval13

Classes in calhoun.analysis.crf.features.interval13 that implement ModelManager

class

Interval13Model

Methods in calhoun.analysis.crf.features.interval13 with parameters of type ModelManager

void	StateTransitionsInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	StateLengthLogprobInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	ReferenceBasePredictorInterval13Base.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	PWMInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	GeneConstraintsInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	ESTInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	BlastInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	PhylogeneticLogprobInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)
void	GapFeaturesInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)
void	FootprintsInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)

Uses of ModelManager in calhoun.analysis.crf.features.interval29

Classes in calhoun.analysis.crf.features.interval29 that implement ModelManager

class

Interval29Model

Methods in calhoun.analysis.crf.features.interval29 with parameters of type ModelManager

void	StateTransitionsInterval29.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	StateLengthLogprobInterval29.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	ReferenceBasePredictorInterval29Base.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	PWMInterval29.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	GeneConstraintsInterval29.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	ESTInterval29.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	GapFeaturesInterval29.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)
void	FootprintsInterval29.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)

Uses of ModelManager in calhoun.analysis.crf.features.supporting.phylogenetic

Methods in calhoun.analysis.crf.features.supporting.phylogenetic with parameters of type ModelManager

void	ColumnConditionalLogProbability.train(ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)

Uses of ModelManager in calhoun.analysis.crf.features.tricycle13

Methods in calhoun.analysis.crf.features.tricycle13 with parameters of type ModelManager

void	IntronLengthFeature.train(int startingIndex, ModelManager modelInfo, java.util.List data)
void	PositionWeightMatrixFeatures.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	MaxentMotifFeatures.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	KmerFeatures.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data) Computes the P(label | kmer) for each kmer across all of the training data.
void	GeneConstraints.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data) Set up the matrix Depends on states starting with the words 'intergenic, intron, and exon'.
void	EmissionMarkovFeature.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	CodingStopFeature.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	PWM_evolution.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	PfamPhase.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	PfamGenic.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	ESTIntron.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	ESTExon.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	ESTEdge.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	IntervalPresenceFeatures.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends IntervalInputSequence.IntervalPosition>> data)
void	GapConjunctionFeatures.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)
void	FelsensteinFeatures.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)

Uses of ModelManager in calhoun.analysis.crf.io

Methods in calhoun.analysis.crf.io that return ModelManager

ModelManager	OutputHandlerGeneCallStats.getManager() gets the model used to generate results
ModelManager	OutputHandlerGeneCallPredict.getManager() gets the model used to generate results

Methods in calhoun.analysis.crf.io with parameters of type ModelManager

void	OutputHandlerGeneCallStats.setManager(ModelManager manager) sets the model used to generate results
void	OutputHandlerGeneCallPredict.setManager(ModelManager manager) sets the model used to generate results

Constructors in calhoun.analysis.crf.io with parameters of type ModelManager

OutputHandlerGeneCallPredict(ModelManager manager, InputHandler inputHandler)
creates an output handler using this model and input handler

OutputHandlerGeneCallStats(ModelManager manager, InputHandler inputHandler)
creates an output handler using this model and input handler

Uses of ModelManager in calhoun.analysis.crf.solver

Methods in calhoun.analysis.crf.solver with parameters of type ModelManager

double[]	TwoPassOptimizer.optimize(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
double[]	StandardOptimizer.optimize(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
double[]	SimplexOptimizer.optimize(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
double[]	SeededOptimizer.optimize(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
double[]	FixedWeightOptimizer.optimize(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
CRFInference.InferenceResult	Viterbi.predict(ModelManager fm, InputSequence<?> seq, double[] lambda)
CRFInference.InferenceResult	SemiMarkovViterbiNoCache.predict(ModelManager fm, InputSequence<?> seq, double[] lambda)
CRFInference.InferenceResult	SemiMarkovViterbi.predict(ModelManager fm, InputSequence<?> seq, double[] lambda)
void	CacheProcessorBasic.setInputData(ModelManager fm, InputSequence<?> seq)
void	CacheProcessor.setInputData(ModelManager fm, InputSequence<?> data)
void	NoCachingCacheProcessor.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	MaximumLikelihoodSemiMarkovGradient.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	MaximumLikelihoodGradient.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	CacheProcessorDeluxe.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	CacheProcessorBasic.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	CacheProcessor.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	CacheProcessor.SolverSetup.setup(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data, boolean allPaths, short[] maxStateLengths2, boolean ignoreSemiMarkovSelfTransitions)

Uses of ModelManager in calhoun.analysis.crf.solver.semimarkov

Methods in calhoun.analysis.crf.solver.semimarkov with parameters of type ModelManager

void	CleanMaximumLikelihoodSemiMarkovGradient.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	CleanLocalScoreSemiMarkovGradient.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)

Uses of ModelManager in calhoun.analysis.crf.test

Classes in calhoun.analysis.crf.test that implement ModelManager

class	ZeroOrderManager
class	ZeroOrderModel

Methods in calhoun.analysis.crf.test with parameters of type ModelManager

void	ConstraintTest.FixedEdges.train(int startingIndex, ModelManager modelInfo, java.util.List data)
void	TestFeatures.TestFeature.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	GeneConstraintsToy.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data) Set up the matrix Depends on states starting with the words 'intergenic, intron, and exon'.