Changeset 6647 for branches/GP.Grammar.Editor/HeuristicLab.Algorithms.DataAnalysis

Timestamp:

08/09/11 11:01:08 (13 years ago)

Author:

mkommend

Message:

#1479: Updated grammar editor branch.

Location:

branches/GP.Grammar.Editor/HeuristicLab.Algorithms.DataAnalysis/3.4

Files:

• CrossValidation.cs (modified) (3 diffs)
• Linear/MultinomialLogitClassification.cs (modified) (1 diff)
• Linear/MultinomialLogitModel.cs (modified) (1 diff)

branches/GP.Grammar.Editor/HeuristicLab.Algorithms.DataAnalysis/3.4/CrossValidation.cs

@@ -446 +446 @@
         // clone models
         var ensembleSolution = new ClassificationEnsembleSolution(
-          solutions.Value.Select(x => cloner.Clone(x.Model)), 
+          solutions.Value.Select(x => cloner.Clone(x.Model)),
           problemDataClone,
           solutions.Value.Select(x => cloner.Clone(x.ProblemData.TrainingPartition)),
@@ -543 +543 @@
         throw new ArgumentException("A cross validation algorithm can only contain DataAnalysisProblems.");
       }
+      algorithm.Problem.Reset += (x,y) => OnProblemChanged();
       problem = (IDataAnalysisProblem)algorithm.Problem;
       OnProblemChanged();
@@ -553 +554 @@
       SamplesStart.Value = 0;
       if (Problem != null) {
-        Problem.ProblemDataChanged += (object sender, EventArgs e) => OnProblemChanged();
         SamplesEnd.Value = Problem.ProblemData.Dataset.Rows;
 

branches/GP.Grammar.Editor/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/MultinomialLogitClassification.cs

@@ -56 +56 @@
     }
 
-    #region logit regression
+    #region logit classification
     protected override void Run() {
       double rmsError, relClassError;
       var solution = CreateLogitClassificationSolution(Problem.ProblemData, out rmsError, out relClassError);
-      Results.Add(new Result(LogitClassificationModelResultName, "The linear regression solution.", solution));
-      Results.Add(new Result("Root mean square error", "The root of the mean of squared errors of the logit regression solution on the training set.", new DoubleValue(rmsError)));
+      Results.Add(new Result(LogitClassificationModelResultName, "The logit classification solution.", solution));
+      Results.Add(new Result("Root mean squared error", "The root of the mean of squared errors of the logit regression solution on the training set.", new DoubleValue(rmsError)));
       Results.Add(new Result("Relative classification error", "Relative classification error on the training set (percentage of misclassified cases).", new PercentValue(relClassError)));
     }

branches/GP.Grammar.Editor/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/MultinomialLogitModel.cs

@@ -66 +66 @@
       targetVariable = original.targetVariable;
       allowedInputVariables = (string[])original.allowedInputVariables.Clone();
-      this.classValues = (double[])original.classValues.Clone();
+      classValues = (double[])original.classValues.Clone();
     }
     public MultinomialLogitModel(alglib.logitmodel logitModel, string targetVariable, IEnumerable<string> allowedInputVariables, double[] classValues)