[shark] 15/58: Minor spell scheck i n description

[Ghislain Vaillant]

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ghisvail-guest pushed a commit to branch master
in repository shark.

commit 37398d35edbb33b1a0e10d19845b6066a16e21de
Author: Jens Holm <jensgholm15 at gmail.com>
Date:   Tue Feb 2 10:49:42 2016 +0100

    Minor spell scheck i n description
---
 .../Algorithms/DirectSearch/CrossEntropyMethod.h   | 42 +++++++++++-----------
 1 file changed, 21 insertions(+), 21 deletions(-)

diff --git a/include/shark/Algorithms/DirectSearch/CrossEntropyMethod.h b/include/shark/Algorithms/DirectSearch/CrossEntropyMethod.h
index 3b5ba9f..5112eca 100644
--- a/include/shark/Algorithms/DirectSearch/CrossEntropyMethod.h
+++ b/include/shark/Algorithms/DirectSearch/CrossEntropyMethod.h
@@ -46,27 +46,27 @@
 namespace shark {
 
 	/**
-	* \brief Implements the Cross Entropy Method.
-	*
-	*  This class implements the noisy cross entropy method 
-	*  as descibed in the following article.
-	*
-	*  Christophe Thiery, Bruno Scherrer. Improvements on Learning Tetris with Cross Entropy.
-	*  International Computer Games Association Journal, ICGA, 2009, 32. <inria-00418930>
-	*
-	*  The algorithm aims to minimize an objective function through stocastic search.
-	*  It works iteratively until a certain stopping criteria is met. At each 
-	*  iteration, it samples a number of vectors from a Gaussian distribution
-	*  and evaluates each of these against the supplied objective function.
-	*  Based on the return value from the objective function a subset if the 
-	*  the best ranked vectors are chosen to update the search parameters 
-	*  of the next generation. 
-	*
-	*  The mean of the Gaussian distribution is set to the centroid of best ranked 
-	*  vectors, and the variance is set to the variance of the best ranked 
-	*  vectors in each individual dimension.
-	*  
-	*/
+	 * \brief Implements the Cross Entropy Method.
+	 *
+	 *  This class implements the noisy cross entropy method 
+	 *  as descibed in the following article.
+	 *
+	 *  Christophe Thiery, Bruno Scherrer. Improvements on Learning Tetris with Cross Entropy.
+	 *  International Computer Games Association Journal, ICGA, 2009, 32. <inria-00418930>
+	 *
+	 *  The algorithm aims to minimize an objective function through stochastic search.
+	 *  It works iteratively until a certain stopping criteria is met. At each 
+	 *  iteration, it samples a number of vectors from a Gaussian distribution
+	 *  and evaluates each of these against the supplied objective function.
+	 *  Based on the return value from the objective function, a subset of the 
+	 *  the best ranked vectors are chosen to update the search parameters 
+	 *  of the next generation. 
+	 *
+	 *  The mean of the Gaussian distribution is set to the centroid of the best ranked 
+	 *  vectors, and the variance is set to the variance of the best ranked 
+	 *  vectors in each individual dimension.
+	 *  
+	 */
 	class CrossEntropyMethod : public AbstractSingleObjectiveOptimizer<RealVector >
 	{
 	public:

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