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Ignore:
Timestamp:
06/27/12 17:34:17 (12 years ago)
Author:
mkommend
Message:

#1722: Renamed indizes to indices in the whole trunk solution.

Location:
trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4
Files:
11 edited

Legend:

Unmodified
Added
Removed

  • trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationEnsembleSolution.cs

    r7259 r8139  
    148148    public override IEnumerable<double> EstimatedTrainingClassValues {
    149149      get {
    150         var rows = ProblemData.TrainingIndizes;
     150        var rows = ProblemData.TrainingIndices;
    151151        var estimatedValuesEnumerators = (from model in Model.Models
    152152                                          select new { Model = model, EstimatedValuesEnumerator = model.GetEstimatedClassValues(ProblemData.Dataset, rows).GetEnumerator() })
    … …  
    167167    public override IEnumerable<double> EstimatedTestClassValues {
    168168      get {
    169         var rows = ProblemData.TestIndizes;
     169        var rows = ProblemData.TestIndices;
    170170        var estimatedValuesEnumerators = (from model in Model.Models
    171171                                          select new { Model = model, EstimatedValuesEnumerator = model.GetEstimatedClassValues(ProblemData.Dataset, rows).GetEnumerator() })
    172172                                         .ToList();
    173         var rowsEnumerator = ProblemData.TestIndizes.GetEnumerator();
     173        var rowsEnumerator = ProblemData.TestIndices.GetEnumerator();
    174174        // aggregate to make sure that MoveNext is called for all enumerators
    175175        while (rowsEnumerator.MoveNext() & estimatedValuesEnumerators.Select(en => en.EstimatedValuesEnumerator.MoveNext()).Aggregate(true, (acc, b) => acc & b)) {

  • trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationSolution.cs

    r7259 r8139  
    5151    }
    5252    public override IEnumerable<double> EstimatedTrainingClassValues {
    53       get { return GetEstimatedClassValues(ProblemData.TrainingIndizes); }
     53      get { return GetEstimatedClassValues(ProblemData.TrainingIndices); }
    5454    }
    5555    public override IEnumerable<double> EstimatedTestClassValues {
    56       get { return GetEstimatedClassValues(ProblemData.TestIndizes); }
     56      get { return GetEstimatedClassValues(ProblemData.TestIndices); }
    5757    }
    5858

  • trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationSolutionBase.cs

    r7259 r8139  
    8787    protected void CalculateResults() {
    8888      double[] estimatedTrainingClassValues = EstimatedTrainingClassValues.ToArray(); // cache values
    89       double[] originalTrainingClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes).ToArray();
     89      double[] originalTrainingClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices).ToArray();
    9090      double[] estimatedTestClassValues = EstimatedTestClassValues.ToArray(); // cache values
    91       double[] originalTestClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndizes).ToArray();
     91      double[] originalTestClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices).ToArray();
    9292
    9393      OnlineCalculatorError errorState;

  • trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/DiscriminantFunctionClassificationSolution.cs

    r7259 r8139  
    5959    }
    6060    public override IEnumerable<double> EstimatedTrainingClassValues {
    61       get { return GetEstimatedClassValues(ProblemData.TrainingIndizes); }
     61      get { return GetEstimatedClassValues(ProblemData.TrainingIndices); }
    6262    }
    6363    public override IEnumerable<double> EstimatedTestClassValues {
    64       get { return GetEstimatedClassValues(ProblemData.TestIndizes); }
     64      get { return GetEstimatedClassValues(ProblemData.TestIndices); }
    6565    }
    6666
    … …  
    8282    }
    8383    public override IEnumerable<double> EstimatedTrainingValues {
    84       get { return GetEstimatedValues(ProblemData.TrainingIndizes); }
     84      get { return GetEstimatedValues(ProblemData.TrainingIndices); }
    8585    }
    8686    public override IEnumerable<double> EstimatedTestValues {
    87       get { return GetEstimatedValues(ProblemData.TestIndizes); }
     87      get { return GetEstimatedValues(ProblemData.TestIndices); }
    8888    }
    8989

  • trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/DiscriminantFunctionClassificationSolutionBase.cs

    r7259 r8139  
    103103    protected void CalculateRegressionResults() {
    104104      double[] estimatedTrainingValues = EstimatedTrainingValues.ToArray(); // cache values
    105       double[] originalTrainingValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes).ToArray();
     105      double[] originalTrainingValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices).ToArray();
    106106      double[] estimatedTestValues = EstimatedTestValues.ToArray(); // cache values
    107       double[] originalTestValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndizes).ToArray();
     107      double[] originalTestValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices).ToArray();
    108108
    109109      OnlineCalculatorError errorState;
    … …  
    140140      double[] classValues;
    141141      double[] thresholds;
    142       var targetClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes);
     142      var targetClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices);
    143143      AccuracyMaximizationThresholdCalculator.CalculateThresholds(ProblemData, EstimatedTrainingValues, targetClassValues, out classValues, out thresholds);
    144144
    … …  
    149149      double[] classValues;
    150150      double[] thresholds;
    151       var targetClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes);
     151      var targetClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices);
    152152      NormalDistributionCutPointsThresholdCalculator.CalculateThresholds(ProblemData, EstimatedTrainingValues, targetClassValues, out classValues, out thresholds);
    153153

  • trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Clustering/ClusteringSolution.cs

    r7259 r8139  
    6868    public virtual IEnumerable<int> TrainingClusterValues {
    6969      get {
    70         return GetClusterValues(ProblemData.TrainingIndizes);
     70        return GetClusterValues(ProblemData.TrainingIndices);
    7171      }
    7272    }
    … …  
    7474    public virtual IEnumerable<int> TestClusterValues {
    7575      get {
    76         return GetClusterValues(ProblemData.TestIndizes);
     76        return GetClusterValues(ProblemData.TestIndices);
    7777      }
    7878    }

  • trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/DataAnalysisProblemData.cs

    r7265 r8139  
    7575    }
    7676
    77     public virtual IEnumerable<int> TrainingIndizes {
     77    public virtual IEnumerable<int> TrainingIndices {
    7878      get {
    7979        return Enumerable.Range(TrainingPartition.Start, Math.Max(0, TrainingPartition.End - TrainingPartition.Start))
    … …  
    8181      }
    8282    }
    83     public virtual IEnumerable<int> TestIndizes {
     83    public virtual IEnumerable<int> TestIndices {
    8484      get {
    8585        return Enumerable.Range(TestPartition.Start, Math.Max(0, TestPartition.End - TestPartition.Start))

  • trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionEnsembleSolution.cs

    r7738 r8139  
    153153    public override IEnumerable<double> EstimatedTrainingValues {
    154154      get {
    155         var rows = ProblemData.TrainingIndizes;
     155        var rows = ProblemData.TrainingIndices;
    156156        var estimatedValuesEnumerators = (from model in Model.Models
    157157                                          select new { Model = model, EstimatedValuesEnumerator = model.GetEstimatedValues(ProblemData.Dataset, rows).GetEnumerator() })
    … …  
    172172    public override IEnumerable<double> EstimatedTestValues {
    173173      get {
    174         var rows = ProblemData.TestIndizes;
     174        var rows = ProblemData.TestIndices;
    175175        var estimatedValuesEnumerators = (from model in Model.Models
    176176                                          select new { Model = model, EstimatedValuesEnumerator = model.GetEstimatedValues(ProblemData.Dataset, rows).GetEnumerator() })
    177177                                         .ToList();
    178         var rowsEnumerator = ProblemData.TestIndizes.GetEnumerator();
     178        var rowsEnumerator = ProblemData.TestIndices.GetEnumerator();
    179179        // aggregate to make sure that MoveNext is called for all enumerators
    180180        while (rowsEnumerator.MoveNext() & estimatedValuesEnumerators.Select(en => en.EstimatedValuesEnumerator.MoveNext()).Aggregate(true, (acc, b) => acc & b)) {

  • trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionSolution.cs

    r7735 r8139  
    5555    }
    5656    public override IEnumerable<double> EstimatedTrainingValues {
    57       get { return GetEstimatedValues(ProblemData.TrainingIndizes); }
     57      get { return GetEstimatedValues(ProblemData.TrainingIndices); }
    5858    }
    5959    public override IEnumerable<double> EstimatedTestValues {
    60       get { return GetEstimatedValues(ProblemData.TestIndizes); }
     60      get { return GetEstimatedValues(ProblemData.TestIndices); }
    6161    }
    6262

  • trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionSolutionBase.cs

    r7735 r8139  
    138138        OnlineCalculatorError errorState;
    139139        Add(new Result(TrainingMeanAbsoluteErrorResultName, "Mean of absolute errors of the model on the training partition", new DoubleValue()));
    140         double trainingMAE = OnlineMeanAbsoluteErrorCalculator.Calculate(EstimatedTrainingValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes), out errorState);
     140        double trainingMAE = OnlineMeanAbsoluteErrorCalculator.Calculate(EstimatedTrainingValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices), out errorState);
    141141        TrainingMeanAbsoluteError = errorState == OnlineCalculatorError.None ? trainingMAE : double.NaN;
    142142      }
    … …  
    145145        OnlineCalculatorError errorState;
    146146        Add(new Result(TestMeanAbsoluteErrorResultName, "Mean of absolute errors of the model on the test partition", new DoubleValue()));
    147         double testMAE = OnlineMeanAbsoluteErrorCalculator.Calculate(EstimatedTestValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndizes), out errorState);
     147        double testMAE = OnlineMeanAbsoluteErrorCalculator.Calculate(EstimatedTestValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices), out errorState);
    148148        TestMeanAbsoluteError = errorState == OnlineCalculatorError.None ? testMAE : double.NaN;
    149149      }
    … …  
    152152        OnlineCalculatorError errorState;
    153153        Add(new Result(TrainingMeanErrorResultName, "Mean of errors of the model on the training partition", new DoubleValue()));
    154         double trainingME = OnlineMeanErrorCalculator.Calculate(EstimatedTrainingValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes), out errorState);
     154        double trainingME = OnlineMeanErrorCalculator.Calculate(EstimatedTrainingValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices), out errorState);
    155155        TrainingMeanError = errorState == OnlineCalculatorError.None ? trainingME : double.NaN;
    156156      }
    … …  
    158158        OnlineCalculatorError errorState;
    159159        Add(new Result(TestMeanErrorResultName, "Mean of errors of the model on the test partition", new DoubleValue()));
    160         double testME = OnlineMeanErrorCalculator.Calculate(EstimatedTestValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndizes), out errorState);
     160        double testME = OnlineMeanErrorCalculator.Calculate(EstimatedTestValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices), out errorState);
    161161        TestMeanError = errorState == OnlineCalculatorError.None ? testME : double.NaN;
    162162      }
    … …  
    166166    protected void CalculateResults() {
    167167      IEnumerable<double> estimatedTrainingValues = EstimatedTrainingValues; // cache values
    168       IEnumerable<double> originalTrainingValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes);
     168      IEnumerable<double> originalTrainingValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices);
    169169      IEnumerable<double> estimatedTestValues = EstimatedTestValues; // cache values
    170       IEnumerable<double> originalTestValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndizes);
     170      IEnumerable<double> originalTestValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices);
    171171
    172172      OnlineCalculatorError errorState;

  • trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/IDataAnalysisProblemData.cs

    r7259 r8139  
    3636    IntRange TestPartition { get; }
    3737
    38     IEnumerable<int> TrainingIndizes { get; }
    39     IEnumerable<int> TestIndizes { get; }
     38    IEnumerable<int> TrainingIndices { get; }
     39    IEnumerable<int> TestIndices { get; }
    4040
    4141    bool IsTrainingSample(int index);
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