Author: erans
Date: Wed Oct 3 18:06:33 2012
New Revision: 1393641
URL: http://svn.apache.org/viewvc?rev=1393641&view=rev
Log:
Improved Javadoc.
Modified:
commons/proper/math/trunk/src/main/java/org/apache/commons/math3/optimization/direct/CMAESOptimizer.java
Modified:
commons/proper/math/trunk/src/main/java/org/apache/commons/math3/optimization/direct/CMAESOptimizer.java
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math3/optimization/direct/CMAESOptimizer.java?rev=1393641&r1=1393640&r2=1393641&view=diff
==============================================================================
---
commons/proper/math/trunk/src/main/java/org/apache/commons/math3/optimization/direct/CMAESOptimizer.java
(original)
+++
commons/proper/math/trunk/src/main/java/org/apache/commons/math3/optimization/direct/CMAESOptimizer.java
Wed Oct 3 18:06:33 2012
@@ -128,9 +128,15 @@ public class CMAESOptimizer
*/
private double[][] boundaries;
/**
- * Individual sigma values - initial search volume. inputSigma determines
- * the initial coordinate wise standard deviations for the search. Setting
- * SIGMA one third of the initial search region is appropriate.
+ * Values in "inputSigma" define the initial coordinate-wise
+ * standard deviations for sampling new search points around the
+ * 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;
/** Number of objective variables/problem dimension */
@@ -252,7 +258,8 @@ public class CMAESOptimizer
/**
* @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) {
this(lambda, inputSigma, DEFAULT_MAXITERATIONS, DEFAULT_STOPFITNESS,
@@ -262,7 +269,8 @@ public class CMAESOptimizer
/**
* @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 stopFitness Whether to stop if objective function value is
smaller than
* {@code stopFitness}.
@@ -287,7 +295,8 @@ public class CMAESOptimizer
/**
* @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 stopFitness Whether to stop if objective function value is
smaller than
* {@code stopFitness}.
