Uses of Class
de.jstacs.classifier.scoringFunctionBased.SFBasedOptimizableFunction

Packages that use SFBasedOptimizableFunction
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 SFBasedOptimizableFunction in de.jstacs.classifier.scoringFunctionBased
 

Methods in de.jstacs.classifier.scoringFunctionBased that return SFBasedOptimizableFunction
protected abstract  SFBasedOptimizableFunction ScoreClassifier.getFunction(Sample[] data, double[][] weights)
          Returns the function that should be optimized.
 

Uses of SFBasedOptimizableFunction in de.jstacs.classifier.scoringFunctionBased.gendismix
 

Subclasses of SFBasedOptimizableFunction in de.jstacs.classifier.scoringFunctionBased.gendismix
 class LogGenDisMixFunction
          This class implements the the following function
\[f(\underline{\lambda}|D,C,\underline{\alpha},\underline{\beta})
The weights $\beta_i$ have to sum to 1.
 

Uses of SFBasedOptimizableFunction in de.jstacs.motifDiscovery
 

Methods in de.jstacs.motifDiscovery with parameters of type SFBasedOptimizableFunction
static boolean MutableMotifDiscovererToolbox.doHeuristicSteps(ScoringFunction[] funs, Sample[] data, double[][] weights, SFBasedOptimizableFunction opt, DifferentiableFunction neg, byte algorithm, double linEps, StartDistanceForecaster startDistance, SafeOutputStream out, boolean breakOnChanged, History[][] hist, int[][] minimalNewLength, boolean maxPos)
          This method tries to make some heuristic step if at least one MutableMotifDiscovererToolbox.InitMethodForScoringFunction is a MutableMotifDiscoverer.
static Sequence[] MutableMotifDiscovererToolbox.enumerate(ScoringFunction[] funs, int[] classIndex, int[] motifIndex, RecyclableSequenceEnumerator[] rse, double weight, SFBasedOptimizableFunction opt, OutputStream out)
          This method allows to enumerate all possible seeds for a number of motifs in the MutableMotifDiscoverers of a specific classes.
static Sequence MutableMotifDiscovererToolbox.enumerate(ScoringFunction[] funs, int classIndex, int motifIndex, RecyclableSequenceEnumerator rse, double weight, SFBasedOptimizableFunction opt, OutputStream out)
          This method allows to enumerate all possible seeds for a motif in the MutableMotifDiscoverer of a specific class.
static boolean MutableMotifDiscovererToolbox.findModification(int clazz, int motif, MutableMotifDiscoverer mmd, ScoringFunction[] score, Sample[] data, SFBasedOptimizableFunction opt, DifferentiableFunction neg, byte algo, double linEps, StartDistanceForecaster startDistance, SafeOutputStream out, History hist, int minimalNewLength, boolean maxPos)
          This method tries to find a modification, i.e. shifting, shrinking, or expanding a motif, that is promising.
static ComparableElement<double[],Double>[] MutableMotifDiscovererToolbox.getSortedInitialParameters(ScoringFunction[] funs, MutableMotifDiscovererToolbox.InitMethodForScoringFunction[] init, SFBasedOptimizableFunction opt, int n, OutputStream stream, int optimizationSteps)
          This method allows to initialize the MutableMotifDiscovererToolbox.InitMethodForScoringFunction using different MutableMotifDiscovererToolbox.InitMethodForScoringFunction.
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.