Changeset 17393

Timestamp:

01/03/20 18:59:45 (5 years ago)

Author:

gkronber

Message:

#2974: fix typos in comments

File:

• branches/2974_Constants_Optimization/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/ConstantsOptimization/LMConstantsOptimizer.cs (modified) (4 diffs)

branches/2974_Constants_Optimization/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/ConstantsOptimization/LMConstantsOptimizer.cs

@@ -47 +47 @@
     /// <param name="rows">The rows for which the data should be extracted.</param>
     /// <param name="applyLinearScaling">A flag to determine whether linear scaling should be applied during the optimization</param>
-    /// <param name="maxIterations">The maximum number of iterations of the Levenberg-Marquard algorithm.</param>
+    /// <param name="maxIterations">The maximum number of iterations of the Levenberg-Marquardt algorithm.</param>
     /// <returns></returns>
     public static double OptimizeConstants(ISymbolicExpressionTree tree,
@@ -63 +63 @@
         throw new NotSupportedException("Could not convert symbolic expression tree to an AutoDiff term due to not supported symbols used in the tree.");
 
-      //Variables of the symbolic expression tree correspond to parameters in the term
-      //Hence if no parameters are present we can't do anything and R² stays the same.
+      // Variables of the symbolic expression tree correspond to parameters in the term.
+      // Hence if no parameters are present we can't do anything and R² stays the same.
       if (term.Parameters.Count == 0) return 0.0;
 
@@ -80 +80 @@
 
     /// <summary>
-    /// Optimizes the numeric coefficents of an AutoDiff Term using the Levenberg-Marquard algorithm.
+    /// Optimizes the numeric coefficents of an AutoDiff Term using the Levenberg-Marquardt algorithm.
     /// </summary>
     /// <param name="term">The AutoDiff term for which the numeric coefficients should be optimized.</param>
@@ -86 +86 @@
     /// <param name="x">The input data for the optimization.</param>
     /// <param name="y">The target values for the optimization.</param>
-    /// <param name="maxIterations">The maximum number of iterations of the Levenberg-Marquard</param>
-    /// <param name="constants">The opitmized constants.</param>
+    /// <param name="maxIterations">The maximum number of iterations of the Levenberg-Marquardt</param>
+    /// <param name="constants">The optimized constants.</param>
     /// <param name="LM_IterationCallback">An optional callback for detailed analysis that is called in each algorithm iteration.</param>
     /// <returns>The R² of the term evaluated on the input data x and the target data y using the optimized constants</returns>