Changeset 6633 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4

Timestamp:

08/04/11 11:22:57 (13 years ago)

Author:

mkommend

Message:

#1475: Minor code changes in multi nominial logit classification classes.

Location:

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

Files:

• MultinomialLogitClassification.cs (modified) (2 diffs)
• MultinomialLogitModel.cs (modified) (1 diff)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/MultinomialLogitClassification.cs

@@ -26 +26 @@
 using HeuristicLab.Core;
 using HeuristicLab.Data;
-using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
 using HeuristicLab.Optimization;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 using HeuristicLab.Problems.DataAnalysis;
-using HeuristicLab.Problems.DataAnalysis.Symbolic;
-using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
 
 namespace HeuristicLab.Algorithms.DataAnalysis {
@@ -59 +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)));
     }

trunk/sources/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)