C# 클래스 MingStar.SimUniversity.AI.Learning.NelderMeadSimplex

공개 메소드들

메소드	설명
Regress ( SimplexConstant simplexConstants, double convergenceTolerance, int maxEvaluations, ObjectiveFunctionDelegate objectiveFunction ) : RegressionResult

메소드	설명
_computeCentroid ( Vector vertices, ErrorProfile errorProfile ) : Vector	Compute the centroid of all points except the worst
_evaluateSimplex ( double errorValues ) : ErrorProfile	Examine all error values to determine the ErrorProfile
_hasConverged ( double convergenceTolerance, ErrorProfile errorProfile, double errorValues ) : bool	Check whether the points in the error profile have so little range that we consider ourselves to have converged
_initializeErrorValues ( Vector vertices, ObjectiveFunctionDelegate objectiveFunction ) : double[]	Evaluate the objective function at each vertex to create a corresponding list of error values for each vertex
_initializeVertices ( SimplexConstant simplexConstants ) : MingStar.SimUniversity.AI.Learning.Vector[]	Construct an initial simplex, given starting guesses for the constants, and initial step sizes for each dimension
_shrinkSimplex ( ErrorProfile errorProfile, Vector vertices, double errorValues, ObjectiveFunctionDelegate objectiveFunction ) : void	Contract the simplex uniformly around the lowest point
_tryToScaleSimplex ( double scaleFactor, ErrorProfile &errorProfile, Vector vertices, double errorValues, ObjectiveFunctionDelegate objectiveFunction ) : double	Test a scaling operation of the high point, and replace it if it is an improvement

public static Regress ( SimplexConstant simplexConstants, double convergenceTolerance, int maxEvaluations, ObjectiveFunctionDelegate objectiveFunction ) : RegressionResult
simplexConstants	SimplexConstant
convergenceTolerance	double
maxEvaluations	int
objectiveFunction	ObjectiveFunctionDelegate
리턴	RegressionResult