Uses of Interface
gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolator

Packages that use LineBracketInterpolator
gov.sandia.cognition.learning.algorithm.minimization.line Provides line (scalar) minimization algorithms. 
gov.sandia.cognition.learning.algorithm.minimization.line.interpolator Provides line (scalar) interpolation/extrapolation algorithms that fit an algebraic function to a (small) collection of data points. 
 

Uses of LineBracketInterpolator in gov.sandia.cognition.learning.algorithm.minimization.line
 

Fields in gov.sandia.cognition.learning.algorithm.minimization.line declared as LineBracketInterpolator
static LineBracketInterpolator<? super DifferentiableUnivariateScalarFunction> LineMinimizerDerivativeBased.DEFAULT_INTERPOLATOR
          Default interpolator to use to create a new candidate point to evaluate
static LineBracketInterpolator<? super Evaluator<Double,Double>> LineMinimizerDerivativeFree.DEFAULT_INTERPOLATOR
          Default interpolation algorithm, LineBracketInterpolatorBrent.
 

Methods in gov.sandia.cognition.learning.algorithm.minimization.line that return LineBracketInterpolator
 LineBracketInterpolator<? super EvaluatorType> AbstractAnytimeLineMinimizer.getInterpolator()
           
 LineBracketInterpolator<? super EvaluatorType> LineMinimizer.getInterpolator()
          Gets the interpolator used to fit data points and derive an interpolated (hypothesized) minimum to try next.
 

Methods in gov.sandia.cognition.learning.algorithm.minimization.line with parameters of type LineBracketInterpolator
 void AbstractAnytimeLineMinimizer.setInterpolator(LineBracketInterpolator<? super EvaluatorType> interpolator)
          Setter for interpolator
 

Constructors in gov.sandia.cognition.learning.algorithm.minimization.line with parameters of type LineBracketInterpolator
AbstractAnytimeLineMinimizer(LineBracketInterpolator<? super EvaluatorType> interpolator)
          Creates a new instance of AbstractAnytimeLineMinimizer
AbstractAnytimeLineMinimizer(LineBracketInterpolator<? super EvaluatorType> interpolator, LineBracket bracket, Double initialGuess, double tolerance, int maxIterations)
          Creates a new instance of AbstractAnytimeLineMinimizer
LineMinimizerDerivativeBased(LineBracketInterpolator<? super DifferentiableUnivariateScalarFunction> interpolator, double minFunctionValue)
          Creates a new instance of LineMinimizerDerivativeBased
LineMinimizerDerivativeFree(LineBracketInterpolator<? super Evaluator<Double,Double>> interpolator)
          Creates a new instance of LineMinimizerDerivativeFree
 

Uses of LineBracketInterpolator in gov.sandia.cognition.learning.algorithm.minimization.line.interpolator
 

Classes in gov.sandia.cognition.learning.algorithm.minimization.line.interpolator that implement LineBracketInterpolator
 class AbstractLineBracketInterpolator<EvaluatorType extends Evaluator<Double,Double>>
          Partial implementation of LinearBracketInterpolator
 class AbstractLineBracketInterpolatorPolynomial<EvaluatorType extends Evaluator<Double,Double>>
          Partial implementation of a LineBracketInterpolator based on a closed-form polynomial function.
 class LineBracketInterpolatorBrent
          Implements Brent's method of function interpolation to find a minimum.
 class LineBracketInterpolatorGoldenSection
          Interpolates between the two bound points of a LineBracket using the golden-section step rule, if that step fails, then the interpolator uses a linear (secant) interpolation.
 class LineBracketInterpolatorHermiteCubic
          Interpolates using a cubic with two points, both of which must have slope information.
 class LineBracketInterpolatorHermiteParabola
          Interpolates using a parabola with two points, at least one of which must have slope information.
 class LineBracketInterpolatorLinear
          Interpolates using a linear (stright-line) curve between two points, neither of which need slope information.
 class LineBracketInterpolatorParabola
          Interpolates using a parabola based on three points without slope information.