Changeset 2440 for trunk/sources/HeuristicLab.SupportVectorMachines

Timestamp:

10/20/09 11:20:13 (15 years ago)

Author:

gkronber

Message:

Fixed #784 (ProblemInjector should be changed to read variable names instead of indexes for input and target variables)

Location:

trunk/sources/HeuristicLab.SupportVectorMachines/3.2

Files:

• PredictorBuilder.cs (modified) (3 diffs)
• SupportVectorCreator.cs (modified) (3 diffs)
• SupportVectorEvaluator.cs (modified) (3 diffs)
• SupportVectorRegression.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.SupportVectorMachines/3.2/PredictorBuilder.cs ¶

@@ -52 +52 @@
       Dataset ds = GetVariableValue<Dataset>("Dataset", scope, true);
       SVMModel model = GetVariableValue<SVMModel>("SVMModel", scope, true);
-      int targetVariable = GetVariableValue<IntData>("TargetVariable", scope, true).Data;
+      string targetVariable = GetVariableValue<StringData>("TargetVariable", scope, true).Data;
       int start = GetVariableValue<IntData>("TrainingSamplesStart", scope, true).Data;
       int end = GetVariableValue<IntData>("TrainingSamplesEnd", scope, true).Data;
@@ -61 +61 @@
       double punishmentFactor = GetVariableValue<DoubleData>("PunishmentFactor", scope, true).Data;
 
-      string targetVariableName = ds.GetVariableName(targetVariable);
+      
       ItemList inputVariables = GetVariableValue<ItemList>("InputVariables", scope, true);
       var inputVariableNames = from x in inputVariables
@@ -69 +69 @@
       double range = ds.GetRange(targetVariable, start, end);
 
-      Predictor predictor = new Predictor(model, targetVariableName, inputVariableNames, minTimeOffset, maxTimeOffset);
+      Predictor predictor = new Predictor(model, targetVariable, inputVariableNames, minTimeOffset, maxTimeOffset);
       predictor.LowerPredictionLimit = mean - punishmentFactor * range;
       predictor.UpperPredictionLimit = mean + punishmentFactor * range;

trunk/sources/HeuristicLab.SupportVectorMachines/3.2/SupportVectorCreator.cs ¶

@@ -40 +40 @@
       //Dataset infos
       AddVariableInfo(new VariableInfo("Dataset", "Dataset with all samples on which to apply the function", typeof(Dataset), VariableKind.In));
-      AddVariableInfo(new VariableInfo("TargetVariable", "Index of the column of the dataset that holds the target variable", typeof(IntData), VariableKind.In));
+      AddVariableInfo(new VariableInfo("TargetVariable", "Name of the target variable", typeof(StringData), VariableKind.In));
       AddVariableInfo(new VariableInfo("InputVariables", "List of allowed input variable names", typeof(ItemList), VariableKind.In));
       AddVariableInfo(new VariableInfo("SamplesStart", "Start index of samples in dataset to evaluate", typeof(IntData), VariableKind.In));
@@ -70 +70 @@
       abortRequested = false;
       Dataset dataset = GetVariableValue<Dataset>("Dataset", scope, true);
-      int targetVariable = GetVariableValue<IntData>("TargetVariable", scope, true).Data;
-      ItemList inputVaribales = GetVariableValue<ItemList>("InputVariables", scope, true);
-      var inputVariableNames = from x in inputVaribales
+      string targetVariable = GetVariableValue<StringData>("TargetVariable", scope, true).Data;
+      int targetVariableIndex = dataset.GetVariableIndex(targetVariable);
+      ItemList inputVariables = GetVariableValue<ItemList>("InputVariables", scope, true);
+      var inputVariableNames = from x in inputVariables
                                select ((StringData)x).Data;
       int start = GetVariableValue<IntData>("SamplesStart", scope, true).Data;
@@ -93 +94 @@
       parameter.Probability = false;
 
-      SVM.Problem problem = SVMHelper.CreateSVMProblem(dataset, targetVariable, inputVariableNames, start, end, minTimeOffset, maxTimeOffset);
+      SVM.Problem problem = SVMHelper.CreateSVMProblem(dataset, targetVariableIndex, inputVariableNames, start, end, minTimeOffset, maxTimeOffset);
       SVM.RangeTransform rangeTransform = SVM.RangeTransform.Compute(problem);
       SVM.Problem scaledProblem = rangeTransform.Scale(problem);

trunk/sources/HeuristicLab.SupportVectorMachines/3.2/SupportVectorEvaluator.cs ¶

@@ -36 +36 @@
       //Dataset infos
       AddVariableInfo(new VariableInfo("Dataset", "Dataset with all samples on which to apply the function", typeof(Dataset), VariableKind.In));
-      AddVariableInfo(new VariableInfo("TargetVariable", "Index of the column of the dataset that holds the target variable", typeof(IntData), VariableKind.In));
+      AddVariableInfo(new VariableInfo("TargetVariable", "Name of the target variable", typeof(StringData), VariableKind.In));
       AddVariableInfo(new VariableInfo("InputVariables", "List of allowed input variable names", typeof(ItemList), VariableKind.In));
       AddVariableInfo(new VariableInfo("SamplesStart", "Start index of samples in dataset to evaluate", typeof(IntData), VariableKind.In));
@@ -52 +52 @@
       var inputVariableNames = from x in inputVariables
                                select ((StringData)x).Data;
-      int targetVariable = GetVariableValue<IntData>("TargetVariable", scope, true).Data;
+      string targetVariable = GetVariableValue<StringData>("TargetVariable", scope, true).Data;
+      int targetVariableIndex = dataset.GetVariableIndex(targetVariable);
       int start = GetVariableValue<IntData>("SamplesStart", scope, true).Data;
       int end = GetVariableValue<IntData>("SamplesEnd", scope, true).Data;
@@ -61 +62 @@
       SVMModel modelData = GetVariableValue<SVMModel>("SVMModel", scope, true);
 
-      SVM.Problem problem = SVMHelper.CreateSVMProblem(dataset, targetVariable, inputVariableNames, start, end, minTimeOffset, maxTimeOffset);
+      SVM.Problem problem = SVMHelper.CreateSVMProblem(dataset, targetVariableIndex, inputVariableNames, start, end, minTimeOffset, maxTimeOffset);
       SVM.Problem scaledProblem = modelData.RangeTransform.Scale(problem);
 
       double[,] values = new double[scaledProblem.Count, 2];
       for (int i = 0; i < scaledProblem.Count; i++) {
-        values[i, 0] = dataset.GetValue(start + i, targetVariable);
+        values[i, 0] = dataset.GetValue(start + i, targetVariableIndex);
         values[i, 1] = SVM.Prediction.Predict(modelData.Model, scaledProblem.X[i]);
       }

trunk/sources/HeuristicLab.SupportVectorMachines/3.2/SupportVectorRegression.cs ¶

@@ -52 +52 @@
     }
 
-    public int TargetVariable {
-      get { return ProblemInjector.GetVariableValue<IntData>("TargetVariable", null, false).Data; }
-      set { ProblemInjector.GetVariableValue<IntData>("TargetVariable", null, false).Data = value; }
+    public string TargetVariable {
+      get { return ProblemInjector.GetVariableValue<StringData>("TargetVariable", null, false).Data; }
+      set { ProblemInjector.GetVariableValue<StringData>("TargetVariable", null, false).Data = value; }
     }
 
@@ -78 +78 @@
       }
     }
-    public IEnumerable<int> AllowedVariables {
+    public IEnumerable<string> AllowedVariables {
       get {
-        ItemList<IntData> allowedVariables = ProblemInjector.GetVariableValue<ItemList<IntData>>("AllowedFeatures", null, false);
+        ItemList<StringData> allowedVariables = ProblemInjector.GetVariableValue<ItemList<StringData>>("AllowedFeatures", null, false);
         return allowedVariables.Select(x => x.Data);
       }
       set {
-        ItemList<IntData> allowedVariables = ProblemInjector.GetVariableValue<ItemList<IntData>>("AllowedFeatures", null, false);
-        foreach (int x in value) allowedVariables.Add(new IntData(x));
+        ItemList<StringData> allowedVariables = ProblemInjector.GetVariableValue<ItemList<StringData>>("AllowedFeatures", null, false);
+        foreach (string x in value) allowedVariables.Add(new StringData(x));
       }
     }