Package 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.

See: Description

Interface Summary

Interface	Description
LineBracketInterpolator<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>>	Definition of an interpolator/extrapolator for a LineBracket.

Class Summary

Class	Description
AbstractLineBracketInterpolator<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>>	Partial implementation of LinearBracketInterpolator
AbstractLineBracketInterpolatorPolynomial<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>>	Partial implementation of a LineBracketInterpolator based on a closed-form polynomial function.
LineBracketInterpolatorBrent	Implements Brent's method of function interpolation to find a minimum.
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.
LineBracketInterpolatorHermiteCubic	Interpolates using a cubic with two points, both of which must have slope information.
LineBracketInterpolatorHermiteParabola	Interpolates using a parabola with two points, at least one of which must have slope information.
LineBracketInterpolatorLinear	Interpolates using a linear (stright-line) curve between two points, neither of which need slope information.
LineBracketInterpolatorParabola	Interpolates using a parabola based on three points without slope information.

Package gov.sandia.cognition.learning.algorithm.minimization.line.interpolator Description

Provides line (scalar) interpolation/extrapolation algorithms that fit an algebraic function to a (small) collection of data points. These algorithms are primarily used as a subroutine in line-search algorithms.

Since:

2.1

Author:

Kevin R. Dixon