Changeset 6685 for branches/GeneralizedQAP/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear

Timestamp:

08/31/11 11:52:11 (13 years ago)

Author:

abeham

Message:

#1628

• Updated branch from trunk
• Changed ReferenceEqualityComparer<T> to become a non-generic class (generic implementation probably was only made because of lacking support for co- and contravariance in C# 3.5)
• Added finished experiment from sample algorithms to the tests
• Wrote a unit test to instantiate every IDeepCloneable type, clone it and compare the objects in the object graph for equal references
• Wrote a unit test to load the experiment, clone it and compare again the objects in the object graph
• Preliminary fix for a potential bug in ThreadSafeLog
• Preliminary fix for a potential bug in OperatorGraphVisualizationInfo
• Preliminary fix for a potential bug in Calculator (and added license headers)
• Preliminary fix for a potential bug in ScrambleMove

Location:

branches/GeneralizedQAP

Files:

• . (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearDiscriminantAnalysis.cs (modified) (1 diff)
• HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearRegression.cs (modified) (1 diff)
• HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/MultinomialLogitClassification.cs (modified) (1 diff)

branches/GeneralizedQAP/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearDiscriminantAnalysis.cs

@@ -106 +106 @@
 
       var model = LinearDiscriminantAnalysis.CreateDiscriminantFunctionModel(tree, new SymbolicDataAnalysisExpressionTreeInterpreter(), problemData, rows);
-      SymbolicDiscriminantFunctionClassificationSolution solution = new SymbolicDiscriminantFunctionClassificationSolution(model, problemData);
+      SymbolicDiscriminantFunctionClassificationSolution solution = new SymbolicDiscriminantFunctionClassificationSolution(model, (IClassificationProblemData)problemData.Clone());
 
       return solution;

branches/GeneralizedQAP/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearRegression.cs

@@ -110 +110 @@
       addition.AddSubtree(cNode);
 
-      SymbolicRegressionSolution solution = new SymbolicRegressionSolution(new SymbolicRegressionModel(tree, new SymbolicDataAnalysisExpressionTreeInterpreter()), problemData);
+      SymbolicRegressionSolution solution = new SymbolicRegressionSolution(new SymbolicRegressionModel(tree, new SymbolicDataAnalysisExpressionTreeInterpreter()), (IRegressionProblemData)problemData.Clone());
       solution.Model.Name = "Linear Regression Model";
       return solution;

branches/GeneralizedQAP/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/MultinomialLogitClassification.cs

@@ -95 +95 @@
       relClassError = alglib.mnlrelclserror(lm, inputMatrix, nRows);
 
-      MultinomialLogitClassificationSolution solution = new MultinomialLogitClassificationSolution(problemData, new MultinomialLogitModel(lm, targetVariable, allowedInputVariables, classValues));
+      MultinomialLogitClassificationSolution solution = new MultinomialLogitClassificationSolution((IClassificationProblemData)problemData.Clone(), new MultinomialLogitModel(lm, targetVariable, allowedInputVariables, classValues));
       return solution;
     }