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Packages that use OptimizableFunction | |
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de.jstacs.classifier.scoringFunctionBased | Provides the classes for Classifier s that are based on ScoringFunction s. |
de.jstacs.classifier.scoringFunctionBased.cll | Provides the implementation of the log conditional likelihood as an OptimizableFunction and a classifier that uses log conditional likelihood or supervised posterior
to learn the parameters of a set of ScoringFunctions |
de.jstacs.motifDiscovery | This package provides the framework including the interface for any de novo motif discoverer |
Uses of OptimizableFunction in de.jstacs.classifier.scoringFunctionBased |
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Subclasses of OptimizableFunction in de.jstacs.classifier.scoringFunctionBased | |
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class |
AbstractOptimizableFunction
This class extends OptimizableFunction and implements some common
methods. |
Methods in de.jstacs.classifier.scoringFunctionBased that return OptimizableFunction | |
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protected abstract OptimizableFunction |
ScoreClassifier.getFunction(Sample[] data,
double[][] weights)
Returns the function that should be optimized. |
Uses of OptimizableFunction in de.jstacs.classifier.scoringFunctionBased.cll |
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Subclasses of OptimizableFunction in de.jstacs.classifier.scoringFunctionBased.cll | |
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class |
NormConditionalLogLikelihood
This class implements the normalized log conditional likelihood. |
Uses of OptimizableFunction in de.jstacs.motifDiscovery |
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Methods in de.jstacs.motifDiscovery with parameters of type OptimizableFunction | |
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static boolean |
MutableMotifDiscovererToolbox.doHeuristicSteps(ScoringFunction[] funs,
Sample[] data,
double[][] weights,
OptimizableFunction opt,
SafeOutputStream out,
boolean breakOnChanged,
History[][] hist,
int[][] minimalNewLength)
This method tries to make some heuristic step if at least one MutableMotifDiscovererToolbox.InitMethodForScoringFunction is a MutableMotifDiscoverer . |
static Sequence |
MutableMotifDiscovererToolbox.enumerate(Sample[] data,
ScoringFunction[] funs,
int classIndex,
int motifIndex,
double weight,
OptimizableFunction opt,
OutputStream out)
This method allows to enumerate all possible seeds for a motif in the HiddenMotifsMixture of a specific class. |
static ComparableElement<double[],Double>[] |
MutableMotifDiscovererToolbox.getSortedInitialParameters(Sample[] data,
ScoringFunction[] funs,
MutableMotifDiscovererToolbox.InitMethodForScoringFunction[] init,
OptimizableFunction opt,
int n,
SafeOutputStream stream)
This method allows to initialize the MutableMotifDiscovererToolbox.InitMethodForScoringFunction using different MutableMotifDiscovererToolbox.InitMethodForScoringFunction . |
static double[][] |
MutableMotifDiscovererToolbox.optimize(ScoringFunction[] funs,
OptimizableFunction opt,
byte algorithm,
double eps,
double linEps,
StartDistanceForecaster startDistance,
SafeOutputStream out,
boolean breakOnChanged,
History[][] hist,
int[][] minimalNewLength,
OptimizableFunction.KindOfParameter plugIn)
This method tries to optimize the problem at hand as good as possible. |
static double[][] |
MutableMotifDiscovererToolbox.optimize(ScoringFunction[] funs,
OptimizableFunction opt,
byte algorithm,
double eps,
double linEps,
StartDistanceForecaster startDistance,
SafeOutputStream out,
boolean breakOnChanged,
History template,
OptimizableFunction.KindOfParameter plugIn)
This method tries to optimize the problem at hand as good as possible. |
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