Changeset 2789

Timestamp:

02/12/10 15:39:18 (15 years ago)

Author:

gkronber

Message:

Fixed #874 (LR doesn't work with an empty set of allowed input variables.)

File:

• trunk/sources/HeuristicLab.LinearRegression/3.2/LinearRegressionOperator.cs (modified) (3 diffs)

trunk/sources/HeuristicLab.LinearRegression/3.2/LinearRegressionOperator.cs

@@ -37 +37 @@
 
     public LinearRegressionOperator() {
+      AddVariableInfo(new VariableInfo("Dataset", "Dataset with all samples on which to apply the function", typeof(Dataset), VariableKind.In));
       AddVariableInfo(new VariableInfo("TargetVariable", "Name of the target variable", typeof(StringData), VariableKind.In));
-      AddVariableInfo(new VariableInfo("Dataset", "Dataset with all samples on which to apply the function", typeof(Dataset), 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));
       AddVariableInfo(new VariableInfo("SamplesEnd", "End index of samples in dataset to evaluate", typeof(IntData), VariableKind.In));
@@ -56 +57 @@
       IntData minTimeOffsetData = GetVariableValue<IntData>("MinTimeOffset", scope, true, false);
       int minTimeOffset = minTimeOffsetData == null ? 0 : minTimeOffsetData.Data;
-
-      IFunctionTree tree = CreateModel(dataset, targetVariable, dataset.VariableNames, start, end, minTimeOffset, maxTimeOffset);
+      ItemList inputVariables = GetVariableValue<ItemList>("InputVariables", scope, true, false);
+      
+      IFunctionTree tree;
+      if (inputVariables != null) {
+        tree = CreateModel(dataset, targetVariable, inputVariables.Cast<StringData>().Select(x => x.Data), start, end, minTimeOffset, maxTimeOffset);
+      } else {
+        tree = CreateModel(dataset, targetVariable, dataset.VariableNames, start, end, minTimeOffset, maxTimeOffset);
+      }
       scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("LinearRegressionModel"), new GeneticProgrammingModel(tree)));
       return null;
@@ -106 +113 @@
       int n = targetVector.Length;
       int p = inputMatrix.GetLength(1);
+      // no features allowed -> return constant offset
+      if (p == 0) return new double[] { Statistics.Mean(targetVector) };
       double[,] dataset = new double[n, p];
       for (int row = 0; row < n; row++) {