Changeset 7099 for branches/HeuristicLab.TimeSeries/HeuristicLab.Algorithms.DataAnalysis

Timestamp:

11/29/11 19:52:22 (13 years ago)

Author:

gkronber

Message:

#1081: merged old changesets r6802, r6807:6808, r6811, r6974, r7058 from the trunk into the TimeSeries branch to bring it to version r7096.

Location:

branches/HeuristicLab.TimeSeries/HeuristicLab.Algorithms.DataAnalysis/3.4

Files:

• HeuristicLab.Algorithms.DataAnalysis-3.4.csproj (modified) (2 diffs)
• Linear/AlglibUtil.cs (modified) (1 diff)
• Linear/LinearTimeSeriesPrognosis.cs (copied) (copied from trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearTimeSeriesPrognosis.cs)
• SupportVectorMachine/SupportVectorRegression.cs (modified) (1 diff)

branches/HeuristicLab.TimeSeries/HeuristicLab.Algorithms.DataAnalysis/3.4/HeuristicLab.Algorithms.DataAnalysis-3.4.csproj

@@ -144 +144 @@
     </Compile>
     <Compile Include="Linear\AlglibUtil.cs" />
+    <Compile Include="Linear\LinearTimeSeriesPrognosis.cs" />
     <Compile Include="Linear\LinearDiscriminantAnalysis.cs" />
     <Compile Include="Linear\LinearRegression.cs">
@@ -247 +248 @@
       <Private>False</Private>
     </ProjectReference>
+    <ProjectReference Include="..\..\HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis\3.4\HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis-3.4.csproj">
+      <Project>{07486E68-1517-4B9D-A58D-A38E99AE71AB}</Project>
+      <Name>HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis-3.4</Name>
+      <Private>False</Private>
+    </ProjectReference>
     <ProjectReference Include="..\..\HeuristicLab.Problems.DataAnalysis.Symbolic\3.4\HeuristicLab.Problems.DataAnalysis.Symbolic-3.4.csproj">
       <Project>{3D28463F-EC96-4D82-AFEE-38BE91A0CA00}</Project>

branches/HeuristicLab.TimeSeries/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/AlglibUtil.cs

@@ -27 +27 @@
   public static class AlglibUtil {
     public static double[,] PrepareInputMatrix(Dataset dataset, IEnumerable<string> variables, IEnumerable<int> rows) {
-      List<string> variablesList = variables.ToList();
+      return PrepareInputMatrix(dataset, variables, rows, new int[] { 0 });
+    }
+
+    public static double[,] PrepareInputMatrix(Dataset dataset, IEnumerable<string> variables, IEnumerable<int> rows, IEnumerable<int> lags) {
+      int maxLag = lags.Max();
+
+      // drop last variable (target variable)
+      List<string> inputVariablesList = variables
+        .Reverse()
+        .Skip(1)
+        .Reverse()
+        .ToList();
+      string targetVariable = variables.Last();
       List<int> rowsList = rows.ToList();
-
-      double[,] matrix = new double[rowsList.Count, variablesList.Count];
+      int nRows = rowsList.Count - maxLag;
+      double[,] matrix = new double[nRows, inputVariablesList.Count * lags.Count() + 1];
 
       int col = 0;
-      foreach (string column in variables) {
-        var values = dataset.GetDoubleValues(column, rows);
-        int row = 0;
-        foreach (var value in values) {
-          matrix[row, col] = value;
-          row++;
+      int row = 0;
+      // input variables
+      foreach (int lag in lags) {
+        foreach (string column in inputVariablesList) {
+          var values = dataset.GetDoubleValues(column, rows.Select(x => x - lag).Take(nRows));
+          row = 0;
+          foreach (var value in values) {
+            if (row >= 0) {
+              matrix[row, col] = value;
+            }
+            row++;
+          }
+          col++;
         }
-        col++;
       }
-
+      // target variable
+      row = 0;
+      foreach (var value in dataset.GetDoubleValues(targetVariable, rows).Take(nRows)) {
+        matrix[row, col] = value;
+        row++;
+      }
       return matrix;
     }

branches/HeuristicLab.TimeSeries/HeuristicLab.Algorithms.DataAnalysis/3.4/SupportVectorMachine/SupportVectorRegression.cs

@@ -143 +143 @@
       parameter.Probability = false;
 
-
       SVM.Problem problem = SupportVectorMachineUtil.CreateSvmProblem(dataset, targetVariable, allowedInputVariables, rows);
       SVM.RangeTransform rangeTransform = SVM.RangeTransform.Compute(problem);