Uses of Class
de.jstacs.classifier.scoringFunctionBased.OptimizableFunction.KindOfParameter

Packages that use OptimizableFunction.KindOfParameter
de.jstacs.classifier.scoringFunctionBased Provides the classes for Classifiers that are based on ScoringFunctions. 
de.jstacs.classifier.scoringFunctionBased.gendismix Provides an implementation of a classifier that allows to train the parameters of a set of NormalizableScoringFunctions 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.classifier.scoringFunctionBased
 

Methods in de.jstacs.classifier.scoringFunctionBased 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.classifier.scoringFunctionBased 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 SFBasedOptimizableFunction.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.classifier.scoringFunctionBased with parameters of type OptimizableFunction.KindOfParameter
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.classifier.scoringFunctionBased.gendismix
 

Constructors in de.jstacs.classifier.scoringFunctionBased.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(ScoringFunction[] funs, SFBasedOptimizableFunction opt, byte algorithm, double eps, 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(ScoringFunction[] funs, SFBasedOptimizableFunction opt, byte algorithm, double eps, 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.