Changeset 15464

Timestamp:

11/08/17 17:01:50 (7 years ago)

Author:

mkommend

Message:

#2854: Corrected results and parameter assignment of random forest model for regression and classification.

Location:

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

Files:

• RandomForestClassification.cs (modified) (2 diffs)
• RandomForestModel.cs (modified) (3 diffs)
• RandomForestRegression.cs (modified) (1 diff)

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

@@ -152 +152 @@
     public static RandomForestClassificationSolution CreateRandomForestClassificationSolution(IClassificationProblemData problemData, int nTrees, double r, double m, int seed,
       out double rmsError, out double relClassificationError, out double outOfBagRmsError, out double outOfBagRelClassificationError) {
-      var model = CreateRandomForestClassificationModel(problemData, nTrees, r, m, seed, out rmsError, out relClassificationError, out outOfBagRmsError, out outOfBagRelClassificationError);
+      var model = CreateRandomForestClassificationModel(problemData, nTrees, r, m, seed,
+        out rmsError, out relClassificationError, out outOfBagRmsError, out outOfBagRelClassificationError);
       return new RandomForestClassificationSolution(model, (IClassificationProblemData)problemData.Clone());
     }
@@ -158 +159 @@
     public static RandomForestModel CreateRandomForestClassificationModel(IClassificationProblemData problemData, int nTrees, double r, double m, int seed,
       out double rmsError, out double relClassificationError, out double outOfBagRmsError, out double outOfBagRelClassificationError) {
-      return RandomForestModel.CreateClassificationModel(problemData, nTrees, r, m, seed, out rmsError, out relClassificationError, out outOfBagRmsError, out outOfBagRelClassificationError);
+      return RandomForestModel.CreateClassificationModel(problemData, nTrees, r, m, seed,
+       rmsError: out rmsError, relClassificationError: out relClassificationError, outOfBagRmsError: out outOfBagRmsError, outOfBagRelClassificationError: out outOfBagRelClassificationError);
     }
     #endregion

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

@@ -288 +288 @@
     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, problemData.TrainingIndices, nTrees, r, m, seed, out rmsError, out avgRelError, out outOfBagAvgRelError, out outOfBagRmsError);
+      return CreateRegressionModel(problemData, problemData.TrainingIndices, nTrees, r, m, seed,
+       rmsError: out rmsError, outOfBagRmsError: out outOfBagRmsError, avgRelError: out avgRelError, outOfBagAvgRelError: out outOfBagAvgRelError);
     }
 
@@ -300 +301 @@
 
       rmsError = rep.rmserror;
+      outOfBagRmsError = rep.oobrmserror;
       avgRelError = rep.avgrelerror;
       outOfBagAvgRelError = rep.oobavgrelerror;
-      outOfBagRmsError = rep.oobrmserror;
 
       return new RandomForestModel(problemData.TargetVariable, dForest, seed, problemData, nTrees, r, m);
@@ -309 +310 @@
     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, problemData.TrainingIndices, nTrees, r, m, seed, out rmsError, out outOfBagRmsError, out relClassificationError, out outOfBagRelClassificationError);
+      return CreateClassificationModel(problemData, problemData.TrainingIndices, nTrees, r, m, seed, 
+        out rmsError, out outOfBagRmsError, out relClassificationError, out outOfBagRelClassificationError);
     }
 

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

@@ -160 +160 @@
       double r, double m, int seed,
       out double rmsError, out double avgRelError, out double outOfBagRmsError, out double outOfBagAvgRelError) {
-      return RandomForestModel.CreateRegressionModel(problemData, nTrees, r, m, seed, out rmsError, out avgRelError, out outOfBagRmsError, out outOfBagAvgRelError);
+      return RandomForestModel.CreateRegressionModel(problemData, nTrees, r, m, seed,
+        rmsError: out rmsError, avgRelError: out avgRelError, outOfBagRmsError: out outOfBagRmsError, outOfBagAvgRelError: out outOfBagAvgRelError);
     }