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Improved Javadoc. 

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1393641 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Gilles Sadowski 2012-10-03 18:06:33 +00:00
parent 8eb3bbaca4
commit e41cea1e33
1 changed files with 15 additions and 6 deletions
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21
src/main/java/org/apache/commons/math3/optimization/direct/CMAESOptimizer.java
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@ -128,9 +128,15 @@ public class CMAESOptimizer
*/ */
private double[][] boundaries; private double[][] boundaries;
/** /**
* Individual sigma values - initial search volume. inputSigma determines * Values in "inputSigma" define the initial coordinate-wise
* the initial coordinate wise standard deviations for the search. Setting * standard deviations for sampling new search points around the
* SIGMA one third of the initial search region is appropriate. * initial guess.
* It is appropriate to set "inputSigma" to the estimated distance
* from the initial to the desired optimum.
* Small values for "inputSigma" induce the search to be more local
* (and very small values are more likely to find a local optimum
* close to the initial guess).
* Too small values might however lead to early termination.
*/ */
private double[] inputSigma; private double[] inputSigma;
/** Number of objective variables/problem dimension */ /** Number of objective variables/problem dimension */
@ -252,7 +258,8 @@ public class CMAESOptimizer
/** /**
* @param lambda Population size. * @param lambda Population size.
* @param inputSigma Initial search volume; sigma of offspring objective variables. * @param inputSigma Initial standard deviations to sample new points
* around the initial guess.
*/ */
public CMAESOptimizer(int lambda, double[] inputSigma) { public CMAESOptimizer(int lambda, double[] inputSigma) {
this(lambda, inputSigma, DEFAULT_MAXITERATIONS, DEFAULT_STOPFITNESS, this(lambda, inputSigma, DEFAULT_MAXITERATIONS, DEFAULT_STOPFITNESS,
@ -262,7 +269,8 @@ public class CMAESOptimizer
/** /**
* @param lambda Population size. * @param lambda Population size.
* @param inputSigma Initial search volume; sigma of offspring objective variables. * @param inputSigma Initial standard deviations to sample new points
* around the initial guess.
* @param maxIterations Maximal number of iterations. * @param maxIterations Maximal number of iterations.
* @param stopFitness Whether to stop if objective function value is smaller than * @param stopFitness Whether to stop if objective function value is smaller than
* {@code stopFitness}. * {@code stopFitness}.
@ -287,7 +295,8 @@ public class CMAESOptimizer
/** /**
* @param lambda Population size. * @param lambda Population size.
* @param inputSigma Initial search volume; sigma of offspring objective variables. * @param inputSigma Initial standard deviations to sample new points
* around the initial guess.
* @param maxIterations Maximal number of iterations. * @param maxIterations Maximal number of iterations.
* @param stopFitness Whether to stop if objective function value is smaller than * @param stopFitness Whether to stop if objective function value is smaller than
* {@code stopFitness}. * {@code stopFitness}.