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Packages that use Function | |
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de.jstacs.algorithms.optimization | Provides classes for different types of algorithms that are not directly linked to the modelling components of Jstacs: Algorithms on graphs, algorithms for numerical optimization, and a basic alignment algorithm. |
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.classifier.scoringFunctionBased.logPrior | Provides a general definition of a parameter log-prior and a number of implementations of Laplace and Gaussian priors |
Uses of Function in de.jstacs.algorithms.optimization |
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Classes in de.jstacs.algorithms.optimization that implement Function | |
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class |
DifferentiableFunction
This class is the framework for any (at least) one time differentiable function f: R^n -> R . |
class |
NegativeDifferentiableFunction
The negative function -f for a given
DifferentiableFunction f . |
class |
NegativeFunction
The negative function -f for a given Function f . |
class |
NegativeOneDimensionalFunction
This class extends the class OneDimensionalFunction . |
class |
NumericalDifferentiableFunction
This class is the framework for any numerical differentiable function f: R^n -> R . |
class |
OneDimensionalFunction
This class implements the interface Function for an one-dimensional
function. |
class |
OneDimensionalSubFunction
This class is used to do the line search. |
class |
QuadraticFunction
This class implements a quadratic function. |
Constructors in de.jstacs.algorithms.optimization with parameters of type Function | |
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NegativeFunction(Function f)
Creates the Function f for which -f
should be calculated. |
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OneDimensionalSubFunction(Function f,
double[] current,
double[] d)
Creates a new OneDimensionalSubFunction from a Function
f for the line search. |
Uses of Function in de.jstacs.classifier.scoringFunctionBased |
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Classes in de.jstacs.classifier.scoringFunctionBased that implement Function | |
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class |
AbstractOptimizableFunction
This class extends OptimizableFunction and implements some common
methods. |
class |
OptimizableFunction
This is the main function for the ScoreClassifier . |
Uses of Function in de.jstacs.classifier.scoringFunctionBased.cll |
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Classes in de.jstacs.classifier.scoringFunctionBased.cll that implement Function | |
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class |
NormConditionalLogLikelihood
This class implements the normalized log conditional likelihood. |
Uses of Function in de.jstacs.classifier.scoringFunctionBased.logPrior |
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Classes in de.jstacs.classifier.scoringFunctionBased.logPrior that implement Function | |
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class |
CompositeLogPrior
This class implements a composite prior that can be used for NormalizableScoringFunction. |
class |
DoesNothingLogPrior
This class defines a LogPrior that does not penalize any parameter. |
class |
LogPrior
The abstract class for any log-prior used e.g. for maximum supervised posterior optimization. |
class |
SeparateGaussianLogPrior
Class for a LogPrior that defines a Gaussian prior on the parameters
of a set of NormalizableScoringFunction s
and a set of class parameters. |
class |
SeparateLaplaceLogPrior
Class for a LogPrior that defines a Laplace prior on the parameters
of a set of NormalizableScoringFunction s
and a set of class parameters. |
class |
SeparateLogPrior
Abstract class for priors that penalize each parameter value independently and have some variances (and possible means) as hyperparameters. |
class |
SimpleGaussianSumLogPrior
This class implements a prior that is a product of Gaussian distributions with mean 0 and equal variance for each parameter. |
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