Uses of Class
de.jstacs.classifiers.differentiableSequenceScoreBased.OptimizableFunction.KindOfParameter

Packages that use OptimizableFunction.KindOfParameter

de.jstacs.classifiers.differentiableSequenceScoreBased	Provides the classes for Classifiers that are based on SequenceScores.
de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix	Provides an implementation of a classifier that allows to train the parameters of a set of DifferentiableStatisticalModels by a unified generative-discriminative learning principle
de.jstacs.motifDiscovery	This package provides the framework including the interface for any de novo motif discoverer

Uses of OptimizableFunction.KindOfParameter in de.jstacs.classifiers.differentiableSequenceScoreBased

Methods in de.jstacs.classifiers.differentiableSequenceScoreBased that return OptimizableFunction.KindOfParameter

protected OptimizableFunction.KindOfParameter	ScoreClassifier.preoptimize(OptimizableFunction f) This method allows to pre-optimize the parameter before the real optimization.
static OptimizableFunction.KindOfParameter	OptimizableFunction.KindOfParameter.valueOf(String name) Returns the enum constant of this type with the specified name.
static OptimizableFunction.KindOfParameter[]	OptimizableFunction.KindOfParameter.values() Returns an array containing the constants of this enum type, in the order they are declared.

Methods in de.jstacs.classifiers.differentiableSequenceScoreBased with parameters of type OptimizableFunction.KindOfParameter

abstract double[]	OptimizableFunction.getParameters(OptimizableFunction.KindOfParameter kind) Returns some parameters that can be used for instance as start parameters.
double[]	AbstractOptimizableFunction.getParameters(OptimizableFunction.KindOfParameter kind)
void	DiffSSBasedOptimizableFunction.getParameters(OptimizableFunction.KindOfParameter kind, double[] erg)
abstract void	AbstractOptimizableFunction.getParameters(OptimizableFunction.KindOfParameter kind, double[] erg) This method enables the user to get the parameters without creating a new array.

Constructors in de.jstacs.classifiers.differentiableSequenceScoreBased with parameters of type OptimizableFunction.KindOfParameter

ScoreClassifierParameterSet(Class<? extends ScoreClassifier> instanceClass, AlphabetContainer alphabet, int length, byte algo, AbstractTerminationCondition tc, double lineps, double startD, boolean free, OptimizableFunction.KindOfParameter kind)
The constructor for a simple, instantiated parameter set.

ScoreClassifierParameterSet(Class<? extends ScoreClassifier> instanceClass, AlphabetContainer alphabet, int length, byte algo, double eps, double lineps, double startD, boolean free, OptimizableFunction.KindOfParameter kind)
The constructor for a simple, instantiated parameter set.

Uses of OptimizableFunction.KindOfParameter in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix

Constructors in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix with parameters of type OptimizableFunction.KindOfParameter

GenDisMixClassifierParameterSet(AlphabetContainer alphabet, int length, byte algo, double eps, double lineps, double startD, boolean free, OptimizableFunction.KindOfParameter kind, boolean norm, int threads)
The default constructor that constructs a new GenDisMixClassifierParameterSet.

GenDisMixClassifierParameterSet(Class<? extends ScoreClassifier> instanceClass, AlphabetContainer alphabet, int length, byte algo, double eps, double lineps, double startD, boolean free, OptimizableFunction.KindOfParameter kind, boolean norm, int threads)
The default constructor that constructs a new GenDisMixClassifierParameterSet.

Uses of OptimizableFunction.KindOfParameter in de.jstacs.motifDiscovery

Methods in de.jstacs.motifDiscovery with parameters of type OptimizableFunction.KindOfParameter

static double[][]

MutableMotifDiscovererToolbox.optimize(DifferentiableSequenceScore[] funs, DiffSSBasedOptimizableFunction opt, byte algorithm, AbstractTerminationCondition condition, double linEps, StartDistanceForecaster startDistance, SafeOutputStream out, boolean breakOnChanged, History[][] hist, int[][] minimalNewLength, OptimizableFunction.KindOfParameter plugIn, boolean maxPos) This method tries to optimize the problem at hand as good as possible.

static double[][]

MutableMotifDiscovererToolbox.optimize(DifferentiableSequenceScore[] funs, DiffSSBasedOptimizableFunction opt, byte algorithm, AbstractTerminationCondition condition, double linEps, StartDistanceForecaster startDistance, SafeOutputStream out, boolean breakOnChanged, History template, OptimizableFunction.KindOfParameter plugIn, boolean maxPos) This method tries to optimize the problem at hand as good as possible.