Improved Javadoc.
git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1393641 13f79535-47bb-0310-9956-ffa450edef68
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@ -128,9 +128,15 @@ public class CMAESOptimizer
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*/
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private double[][] boundaries;
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/**
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* Individual sigma values - initial search volume. inputSigma determines
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* the initial coordinate wise standard deviations for the search. Setting
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* SIGMA one third of the initial search region is appropriate.
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* Values in "inputSigma" define the initial coordinate-wise
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* standard deviations for sampling new search points around the
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* initial guess.
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* It is appropriate to set "inputSigma" to the estimated distance
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* from the initial to the desired optimum.
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* Small values for "inputSigma" induce the search to be more local
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* (and very small values are more likely to find a local optimum
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* close to the initial guess).
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* Too small values might however lead to early termination.
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*/
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private double[] inputSigma;
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/** Number of objective variables/problem dimension */
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@ -252,7 +258,8 @@ public class CMAESOptimizer
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/**
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* @param lambda Population size.
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* @param inputSigma Initial search volume; sigma of offspring objective variables.
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* @param inputSigma Initial standard deviations to sample new points
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* around the initial guess.
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*/
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public CMAESOptimizer(int lambda, double[] inputSigma) {
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this(lambda, inputSigma, DEFAULT_MAXITERATIONS, DEFAULT_STOPFITNESS,
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@ -262,7 +269,8 @@ public class CMAESOptimizer
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/**
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* @param lambda Population size.
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* @param inputSigma Initial search volume; sigma of offspring objective variables.
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* @param inputSigma Initial standard deviations to sample new points
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* around the initial guess.
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* @param maxIterations Maximal number of iterations.
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* @param stopFitness Whether to stop if objective function value is smaller than
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* {@code stopFitness}.
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@ -287,7 +295,8 @@ public class CMAESOptimizer
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/**
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* @param lambda Population size.
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* @param inputSigma Initial search volume; sigma of offspring objective variables.
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* @param inputSigma Initial standard deviations to sample new points
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* around the initial guess.
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* @param maxIterations Maximal number of iterations.
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* @param stopFitness Whether to stop if objective function value is smaller than
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* {@code stopFitness}.
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