Changeset 11343 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/RandomForest/RandomForestModel.cs

Timestamp:

09/04/14 17:31:46 (10 years ago)

Author:

mkommend

Message:

#2237: Corrected newly introduced bug in RandomForestModel and reorganized RandomForestUtil.

File:

• trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/RandomForest/RandomForestModel.cs (modified) (3 diffs)

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

@@ -189 +189 @@
     public static RandomForestModel CreateRegressionModel(IRegressionProblemData problemData, int nTrees, double r, double m, int seed,
       out double rmsError, out double outOfBagRmsError, out double avgRelError, out double outOfBagAvgRelError) {
-      return CreateRegressionModel(problemData, nTrees, r, m, seed, out rmsError, out avgRelError, out outOfBagAvgRelError, out outOfBagRmsError, problemData.TrainingIndices);
-    }
-
-    public static RandomForestModel CreateRegressionModel(IRegressionProblemData problemData, int nTrees, double r, double m, int seed,
-      out double rmsError, out double outOfBagRmsError, out double avgRelError, out double outOfBagAvgRelError, IEnumerable<int> trainingIndices) {
+      return CreateRegressionModel(problemData, problemData.TrainingIndices, nTrees, r, m, seed, out rmsError, out avgRelError, out outOfBagAvgRelError, out outOfBagRmsError);
+    }
+
+    public static RandomForestModel CreateRegressionModel(IRegressionProblemData problemData, IEnumerable<int> trainingIndices, int nTrees, double r, double m, int seed,
+      out double rmsError, out double outOfBagRmsError, out double avgRelError, out double outOfBagAvgRelError) {
       var variables = problemData.AllowedInputVariables.Concat(new string[] { problemData.TargetVariable });
-      double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(problemData.Dataset, variables, problemData.TrainingIndices);
+      double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(problemData.Dataset, variables, trainingIndices);
 
       alglib.dfreport rep;
@@ -205 +205 @@
       outOfBagRmsError = rep.oobrmserror;
 
-      return new RandomForestModel(dForest,
-        seed, problemData,
-        nTrees, r, m);
+      return new RandomForestModel(dForest,seed, problemData,nTrees, r, m);
     }
 
     public static RandomForestModel CreateClassificationModel(IClassificationProblemData problemData, int nTrees, double r, double m, int seed,
       out double rmsError, out double outOfBagRmsError, out double relClassificationError, out double outOfBagRelClassificationError) {
-      return CreateClassificationModel(problemData, nTrees, r, m, seed, out rmsError, out outOfBagRmsError, out relClassificationError, out outOfBagRelClassificationError, problemData.TrainingIndices);
-    }
-
-    public static RandomForestModel CreateClassificationModel(IClassificationProblemData problemData, int nTrees, double r, double m, int seed,
-      out double rmsError, out double outOfBagRmsError, out double relClassificationError, out double outOfBagRelClassificationError, IEnumerable<int> trainingIndices) {
+      return CreateClassificationModel(problemData, problemData.TrainingIndices, nTrees, r, m, seed, out rmsError, out outOfBagRmsError, out relClassificationError, out outOfBagRelClassificationError);
+    }
+
+    public static RandomForestModel CreateClassificationModel(IClassificationProblemData problemData, IEnumerable<int> trainingIndices, int nTrees, double r, double m, int seed,
+      out double rmsError, out double outOfBagRmsError, out double relClassificationError, out double outOfBagRelClassificationError) {
 
       var variables = problemData.AllowedInputVariables.Concat(new string[] { problemData.TargetVariable });
@@ -244 +242 @@
       outOfBagRelClassificationError = rep.oobrelclserror;
 
-      return new RandomForestModel(dForest,
-        seed, problemData,
-        nTrees, r, m, classValues);
+      return new RandomForestModel(dForest,seed, problemData,nTrees, r, m, classValues);
     }