Context Navigation

← Previous Change
Next Change →

Changeset 6760 for branches/PersistenceSpeedUp/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression

Timestamp:

09/14/11 13:59:25 (13 years ago)

Author:

epitzer

Message:

#1530 integrate changes from trunk

Location:

branches/PersistenceSpeedUp

Files:

: 13 edited
: 1 copied

Legend:

: Unmodified
: Added
: Removed

branches/PersistenceSpeedUp

Property svn:ignore

old	new
12	12	*.psess
13	13	*.vsp
	14	*.docstates

Property svn:mergeinfo changed

/branches/QAPAlgorithms (added)	merged: 6350-6351,6355,6416,6569-6570,6586,6593-6594,6610-6611,6615-6617,6627
/branches/histogram (added)	merged: 5959,5961,5970,5994-5996,5999,6007,6010-6016,6020,6022,6027-6028,6032,6046,6055-6056,6081-6082,6086-6087,6089,6115,6176,6194-6195,6338-6341
/trunk/sources	merged: 6233-6241,6250,6252,6254-6256,6259,6262,6265,6291,6298,6302,6342,6344,6352-6353,6356,6363,6365,6375-6376,6378,6380,6410-6411,6413,6423-6425,6427-6430,6432,6434,6436,6438-6443,6446-6450,6455,6459-6460,6466-6468,6470-6472,6474,6476-6477,6485,6487-6488,6491,6495-6496,6498-6520,6522-6527,6529,6531-6545,6547-6555,6557-6559,6566-6568,6571-6585,6587-6592,6596-6606,6609,6612-6614,6628-6631,6633-6638,6640-6645,6648-6649,6652-6656,6661-6674,6676-6681,6684,6686-6687,6690-6695,6697,6705,6709,6718-6720,6728-6729,6732,6735,6738-6742,6745-6746,6749-6750,6754-6755,6758

branches/PersistenceSpeedUp/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression-3.4.csproj

r5809	r6760
109	109	<ItemGroup>
110	110	<Compile Include="MultiObjective\SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer.cs" />
	111	<Compile Include="SingleObjective\SymbolicRegressionConstantOptimizationEvaluator.cs" />
111	112	<Compile Include="SingleObjective\SymbolicRegressionSingleObjectiveOverfittingAnalyzer.cs" />
112	113	<Compile Include="SymbolicRegressionModel.cs" />

branches/PersistenceSpeedUp/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/HeuristicLabProblemsDataAnalysisSymbolicRegressionPlugin.cs.frame

r6139	r6760
26	26
27	27	namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
28		[Plugin("HeuristicLab.Problems.DataAnalysis.Symbolic.Regression","Provides classes to perform symbolic regression (single- or multiobjective).", "3.4.0.$WCREV$")]
	28	[Plugin("HeuristicLab.Problems.DataAnalysis.Symbolic.Regression","Provides classes to perform symbolic regression (single- or multiobjective).", "3.4.1.$WCREV$")]
29	29	[PluginFile("HeuristicLab.Problems.DataAnalysis.Symbolic.Regression-3.4.dll", PluginFileType.Assembly)]
30	30	[PluginDependency("HeuristicLab.ALGLIB", "3.1")]

branches/PersistenceSpeedUp/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectiveMeanSquaredErrorTreeSizeEvaluator.cs

r5942	r6760
54	54	public static double[] Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows) {
55	55	IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
56		IEnumerable<double> originalValues = problemData.Dataset.Get~~EnumeratedVaria~~bleValues(problemData.TargetVariable, rows);
	56	IEnumerable<double> originalValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows);
57	57	IEnumerable<double> boundedEstimationValues = estimatedValues.LimitToRange(lowerEstimationLimit, upperEstimationLimit);
58	58	OnlineCalculatorError errorState;

branches/PersistenceSpeedUp/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs

r5942	r6760
54	54	public static double[] Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows) {
55	55	IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
56		IEnumerable<double> originalValues = problemData.Dataset.Get~~EnumeratedVaria~~bleValues(problemData.TargetVariable, rows);
	56	IEnumerable<double> originalValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows);
57	57	OnlineCalculatorError errorState;
58	58	double r2 = OnlinePearsonsRSquaredCalculator.Calculate(estimatedValues, originalValues, out errorState);

branches/PersistenceSpeedUp/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectiveProblem.cs

-                      r5854
+                      r6760
     private void UpdateEstimationLimits() {
       if (ProblemData.TrainingPartition.Start < ProblemData.TrainingPartition.End) {
         var targetValues = ProblemData.Dataset.GetVariableValues(ProblemData.TargetVariable, ProblemData.TrainingPartition.Start, ProblemData.TrainingPartition.End);
+      if (ProblemData.TrainingIndizes.Any()) {
+        var targetValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes).ToList();
         var mean = targetValues.Average();
         var range = targetValues.Max() - targetValues.Min();
         EstimationLimits.Upper = mean + PunishmentFactor * range;
         EstimationLimits.Lower = mean - PunishmentFactor * range;
+      } else {
+        EstimationLimits.Upper = double.MaxValue;
+        EstimationLimits.Lower = double.MinValue;
+      }
+    }

branches/PersistenceSpeedUp/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/Properties/AssemblyInfo.frame

r6139	r6760
53	53	// by using the '*' as shown below:
54	54	[assembly: AssemblyVersion("3.4.0.0")]
55		[assembly: AssemblyFileVersion("3.4.0.$WCREV$")]
	55	[assembly: AssemblyFileVersion("3.4.1.$WCREV$")]

branches/PersistenceSpeedUp/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator.cs

r5942	r6760
56	56	public static double Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows) {
57	57	IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
58		IEnumerable<double> originalValues = problemData.Dataset.Get~~EnumeratedVaria~~bleValues(problemData.TargetVariable, rows);
	58	IEnumerable<double> originalValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows);
59	59	IEnumerable<double> boundedEstimationValues = estimatedValues.LimitToRange(lowerEstimationLimit, upperEstimationLimit);
60	60	OnlineCalculatorError errorState;

branches/PersistenceSpeedUp/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveOverfittingAnalyzer.cs

-                      r5907
+                      r6760
       double[] trainingQuality = QualityParameter.ActualValue.Select(x => x.Value).ToArray();
+      var problemData = ProblemDataParameter.ActualValue;
+      var evaluator = EvaluatorParameter.ActualValue;
       // evaluate on validation partition
+      IExecutionContext childContext = (IExecutionContext)ExecutionContext.CreateChildOperation(EvaluatorParameter.ActualValue);
+      double[] validationQuality = (from tree in SymbolicExpressionTree
+                                    select EvaluatorParameter.ActualValue.Evaluate(childContext, tree, ProblemDataParameter.ActualValue, rows))
+                                   .ToArray();
+      IExecutionContext childContext = (IExecutionContext)ExecutionContext.CreateChildOperation(evaluator);
+      double[] validationQuality = SymbolicExpressionTree
+        .AsParallel()
+        .Select(t => evaluator.Evaluate(childContext, t, problemData, rows))
+        .ToArray();
       double r = 0.0;
       try {

branches/PersistenceSpeedUp/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.cs

r5942	r6760
56	56	public static double Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows) {
57	57	IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
58		IEnumerable<double> originalValues = problemData.Dataset.Get~~EnumeratedVaria~~bleValues(problemData.TargetVariable, rows);
	58	IEnumerable<double> originalValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows);
59	59	OnlineCalculatorError errorState;
60	60	double r2 = OnlinePearsonsRSquaredCalculator.Calculate(estimatedValues, originalValues, out errorState);

branches/PersistenceSpeedUp/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveProblem.cs

-                      r5854
+                      r6760
     private void UpdateEstimationLimits() {
       if (ProblemData.TrainingPartition.Start < ProblemData.TrainingPartition.End) {
         var targetValues = ProblemData.Dataset.GetVariableValues(ProblemData.TargetVariable, ProblemData.TrainingPartition.Start, ProblemData.TrainingPartition.End);
+      if (ProblemData.TrainingIndizes.Any()) {
+        var targetValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes).ToList();
         var mean = targetValues.Average();
         var range = targetValues.Max() - targetValues.Min();
         EstimationLimits.Upper = mean + PunishmentFactor * range;
         EstimationLimits.Lower = mean - PunishmentFactor * range;
+      } else {
+        EstimationLimits.Upper = double.MaxValue;
+        EstimationLimits.Lower = double.MinValue;
+      }
+    }

branches/PersistenceSpeedUp/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionModel.cs

-                      r5942
+                      r6760
   /// </summary>
   [StorableClass]
   [Item(Name = "SymbolicRegressionModel", Description = "Represents a symbolic regression model.")]
+  [Item(Name = "Symbolic Regression Model", Description = "Represents a symbolic regression model.")]
   public class SymbolicRegressionModel : SymbolicDataAnalysisModel, ISymbolicRegressionModel {
     [Storable]
 …
+    }
+    public ISymbolicRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
+      return new SymbolicRegressionSolution(this, problemData);
+    }
+    IRegressionSolution IRegressionModel.CreateRegressionSolution(IRegressionProblemData problemData) {
+      return CreateRegressionSolution(problemData);
+    }
     public static void Scale(SymbolicRegressionModel model, IRegressionProblemData problemData) {
       var dataset = problemData.Dataset;
 …
       var rows = problemData.TrainingIndizes;
       var estimatedValues = model.Interpreter.GetSymbolicExpressionTreeValues(model.SymbolicExpressionTree, dataset, rows);
       var targetValues = dataset.GetEnumeratedVariableValues(targetVariable, rows);
+      var targetValues = dataset.GetDoubleValues(targetVariable, rows);
       double alpha;
       double beta;
 …
         var mainBranch = startNode.GetSubtree(0);
         startNode.RemoveSubtree(0);
         var scaledMainBranch = MakeSum(MakeProduct(beta, mainBranch), alpha);
+        var scaledMainBranch = MakeSum(MakeProduct(mainBranch, beta), alpha);
         startNode.AddSubtree(scaledMainBranch);
+      }
 …
         return treeNode;
       } else {
+        var node = (new Addition()).CreateTreeNode();
+        var addition = new Addition();
+        var node = addition.CreateTreeNode();
         var alphaConst = MakeConstant(alpha);
         node.AddSubtree(treeNode);
 …
+    }
     private static ISymbolicExpressionTreeNode MakeProduct(double beta, ISymbolicExpressionTreeNode treeNode) {
+    private static ISymbolicExpressionTreeNode MakeProduct(ISymbolicExpressionTreeNode treeNode, double beta) {
       if (beta.IsAlmost(1.0)) {
         return treeNode;
       } else {
+        var node = (new Multiplication()).CreateTreeNode();
+        var multipliciation = new Multiplication();
+        var node = multipliciation.CreateTreeNode();
         var betaConst = MakeConstant(beta);
         node.AddSubtree(treeNode);

branches/PersistenceSpeedUp/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionSolution.cs

-                      r5975
+                      r6760
 #endregion
-using System;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
 …
+    }
+    protected override void OnModelChanged(EventArgs e) {
+      base.OnModelChanged(e);
+      RecalculateResults();
+    }
+    private new void RecalculateResults() {
+    protected override void RecalculateResults() {
+      base.RecalculateResults();
       ModelLength = Model.SymbolicExpressionTree.Length;
       ModelDepth = Model.SymbolicExpressionTree.Depth;

Note: See TracChangeset for help on using the changeset viewer.

Download in other formats:

Update cookies preferences