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

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 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 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 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.