Package | Description |
---|---|
de.jstacs.classifiers.differentiableSequenceScoreBased |
Provides the classes for
Classifier s that are based on SequenceScore s.It includes a sub-package for discriminative objective functions, namely conditional likelihood and supervised posterior, and a separate sub-package for the parameter priors, that can be used for the supervised posterior. |
de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix |
Provides an implementation of a classifier that allows to train the parameters of a set of
DifferentiableStatisticalModel s by
a unified generative-discriminative learning principle. |
de.jstacs.motifDiscovery |
This package provides the framework including the interface for any de novo motif discoverer.
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Modifier and Type | Method and Description |
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protected OptimizableFunction.KindOfParameter |
ScoreClassifier.preoptimize(OptimizableFunction f)
This method allows to pre-optimize the parameter before the real optimization.
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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.
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Modifier and Type | Method and Description |
---|---|
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.
|
Constructor and Description |
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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.
|
Constructor and Description |
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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 . |
Modifier and Type | Method and Description |
---|---|
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.
|