Uses of Interface
de.jstacs.algorithms.optimization.Function

Packages that use Function

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 Classifiers that are based on ScoringFunctions.
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

Classes in de.jstacs.algorithms.optimization that implement Function

class	DifferentiableFunction This class is the framework for any (at least) one time differentiable function f: R^n -> R.
class	NegativeDifferentiableFunction The function -f for a given function f.
class	NegativeFunction The Function -f for a given function f.
class	NegativeOneDimensionalFunction This class extends the class OneDimensionalFunction.
class	NumericalDifferentiableFunction This class is the framework for any function f: R^n -> R.
class	OneDimensionalFunction This class implements the interface function for an one-dimensional function.
class	OneDimensionalSubFunction This class 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

NegativeFunction(Function f)
Creates the function f for which -f should be calculated.

OneDimensionalSubFunction(Function f, double[] current, double[] d)

Uses of Function in de.jstacs.classifier.scoringFunctionBased

Classes in de.jstacs.classifier.scoringFunctionBased that implement Function

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

Classes in de.jstacs.classifier.scoringFunctionBased.cll that implement Function

class

NormConditionalLogLikelihood This class implements the normalized log conditional likelihood.

Uses of Function in de.jstacs.classifier.scoringFunctionBased.logPrior

Classes in de.jstacs.classifier.scoringFunctionBased.logPrior that implement Function

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 NormalizableScoringFunctions and a set of class parameters.
class	SeparateLaplaceLogPrior Class for a LogPrior that defines a Laplace prior on the parameters of a set of NormalizableScoringFunctions and a set of class parameters.
class	SeparateLogPrior Abstract class for priors that penalize each parameter value independently and have some variance (and possible mean) 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.