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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:
2 edited

Legend:

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

    r6576 r6633  
    2626using HeuristicLab.Core;
    2727using HeuristicLab.Data;
    28 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
    2928using HeuristicLab.Optimization;
    3029using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
    3130using HeuristicLab.Problems.DataAnalysis;
    32 using HeuristicLab.Problems.DataAnalysis.Symbolic;
    33 using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
    3431
    3532namespace HeuristicLab.Algorithms.DataAnalysis {
     
    5956    }
    6057
    61     #region logit regression
     58    #region logit classification
    6259    protected override void Run() {
    6360      double rmsError, relClassError;
    6461      var solution = CreateLogitClassificationSolution(Problem.ProblemData, out rmsError, out relClassError);
    65       Results.Add(new Result(LogitClassificationModelResultName, "The linear regression solution.", solution));
    66       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)));
     62      Results.Add(new Result(LogitClassificationModelResultName, "The logit classification solution.", solution));
     63      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)));
    6764      Results.Add(new Result("Relative classification error", "Relative classification error on the training set (percentage of misclassified cases).", new PercentValue(relClassError)));
    6865    }
  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/MultinomialLogitModel.cs

    r6604 r6633  
    6666      targetVariable = original.targetVariable;
    6767      allowedInputVariables = (string[])original.allowedInputVariables.Clone();
    68       this.classValues = (double[])original.classValues.Clone();
     68      classValues = (double[])original.classValues.Clone();
    6969    }
    7070    public MultinomialLogitModel(alglib.logitmodel logitModel, string targetVariable, IEnumerable<string> allowedInputVariables, double[] classValues)
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