Changeset 14107 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/RandomForest

Timestamp:

07/18/16 17:45:45 (8 years ago)

Author:

pfleck

Message:

#2631

• Added an additional function to ALGLIB that returns the prediction for each tree of a decision forest.
• Implemented IConfidenceRegression/Solution for RandomForestModel/Solution using the variance of the predictions from the trees.

Location:

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/RandomForest

Files:

• RandomForestModel.cs (modified) (1 diff)
• RandomForestRegressionSolution.cs (modified) (1 diff)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/RandomForest/RandomForestModel.cs

@@ -152 +152 @@
     }
 
+    public IEnumerable<double> GetEstimatedVariances(IDataset dataset, IEnumerable<int> rows) {
+      double[,] inputData = AlglibUtil.PrepareInputMatrix(dataset, AllowedInputVariables, rows);
+      AssertInputMatrix(inputData);
+
+      int n = inputData.GetLength(0);
+      int columns = inputData.GetLength(1);
+      double[] x = new double[columns];
+      double[] ys = new double[columns];
+
+      for (int row = 0; row < n; row++) {
+        for (int column = 0; column < columns; column++) {
+          x[column] = inputData[row, column];
+        }
+        alglib.dforest.dfprocessraw(RandomForest.innerobj, x, ref ys);
+        yield return ys.VariancePop();
+      }
+    }
+
     public override IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) {
       double[,] inputData = AlglibUtil.PrepareInputMatrix(dataset, AllowedInputVariables, rows);

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/RandomForest/RandomForestRegressionSolution.cs

@@ -31 +31 @@
   [Item("RandomForestRegressionSolution", "Represents a random forest solution for a regression problem which can be visualized in the GUI.")]
   [StorableClass]
-  public sealed class RandomForestRegressionSolution : RegressionSolution, IRandomForestRegressionSolution {
+  public sealed class RandomForestRegressionSolution : ConfidenceRegressionSolution, IRandomForestRegressionSolution {
 
     public new IRandomForestModel Model {