Changeset 2440 for trunk/sources/HeuristicLab.SupportVectorMachines/3.2/SupportVectorEvaluator.cs

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)

File:

• trunk/sources/HeuristicLab.SupportVectorMachines/3.2/SupportVectorEvaluator.cs (modified) (3 diffs)

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]);
       }