Free cookie consent management tool by TermsFeed Policy Generator

Ignore:
Timestamp:
05/03/16 09:47:26 (8 years ago)
Author:
pfleck
Message:

#2597:

  • Added new interface IConfidenceBoundRegressionModel and IConfidenceBoundRegressionSolution for regression models/solutions that support confidence information on estimated samples.
  • Renamed GetEstimatedVariance to GetEstimatedVariances to be consistent with GetEstimatedValues.
Location:
branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Algorithms.DataAnalysis.Views/3.4
Files:
3 edited

Legend:

Unmodified
Added
Removed

  • branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/GaussianProcessRegressionSolutionEstimatedValuesView.cs

    r13592 r13823  
    5353      var testRows = Content.ProblemData.TestIndices;
    5454
    55       var estimated_var_training = Content.GetEstimatedVariance(trainingRows).GetEnumerator();
    56       var estimated_var_test = Content.GetEstimatedVariance(testRows).GetEnumerator();
     55      var estimated_var_training = Content.GetEstimatedVariances(trainingRows).GetEnumerator();
     56      var estimated_var_test = Content.GetEstimatedVariances(testRows).GetEnumerator();
    5757
    5858      foreach (var row in Content.ProblemData.TrainingIndices) {

  • branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/GaussianProcessRegressionSolutionInteractiveRangeEstimatorView.cs

    r13816 r13823  
    114114      var model = Content.Model;
    115115      var means = model.GetEstimatedValues(dataset, Enumerable.Range(0, DrawingSteps)).ToList();
    116       var variances = model.GetEstimatedVariance(dataset, Enumerable.Range(0, DrawingSteps)).ToList();
     116      var variances = model.GetEstimatedVariances(dataset, Enumerable.Range(0, DrawingSteps)).ToList();
    117117
    118118      // Charting config

  • branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/GaussianProcessRegressionSolutionLineChartView.cs

    r13121 r13823  
    6969        this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].EmptyPointStyle.Color = this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Color;
    7070        var mean = Content.EstimatedTrainingValues.ToArray();
    71         var s2 = Content.EstimatedTrainingVariance.ToArray();
     71        var s2 = Content.EstimatedTrainingVariances.ToArray();
    7272        var lower = mean.Zip(s2, GetLowerConfBound).ToArray();
    7373        var upper = mean.Zip(s2, GetUpperConfBound).ToArray();
    … …  
    8282
    8383        mean = Content.EstimatedTestValues.ToArray();
    84         s2 = Content.EstimatedTestVariance.ToArray();
     84        s2 = Content.EstimatedTestVariances.ToArray();
    8585        lower = mean.Zip(s2, GetLowerConfBound).ToArray();
    8686        upper = mean.Zip(s2, GetUpperConfBound).ToArray();
    … …  
    9292        int[] allIndices = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndices).Except(Content.ProblemData.TestIndices).ToArray();
    9393        mean = Content.EstimatedValues.ToArray();
    94         s2 = Content.EstimatedVariance.ToArray();
     94        s2 = Content.EstimatedVariances.ToArray();
    9595        lower = mean.Zip(s2, GetLowerConfBound).ToArray();
    9696        upper = mean.Zip(s2, GetUpperConfBound).ToArray();
    … …  
    264264            indices = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndices).Except(Content.ProblemData.TestIndices).ToArray();
    265265            mean = Content.EstimatedValues.ToArray();
    266             s2 = Content.EstimatedVariance.ToArray();
     266            s2 = Content.EstimatedVariances.ToArray();
    267267            lower = mean.Zip(s2, GetLowerConfBound).ToArray();
    268268            upper = mean.Zip(s2, GetUpperConfBound).ToArray();
    … …  
    273273            indices = Content.ProblemData.TrainingIndices.ToArray();
    274274            mean = Content.EstimatedTrainingValues.ToArray();
    275             s2 = Content.EstimatedTrainingVariance.ToArray();
     275            s2 = Content.EstimatedTrainingVariances.ToArray();
    276276            lower = mean.Zip(s2, GetLowerConfBound).ToArray();
    277277            upper = mean.Zip(s2, GetUpperConfBound).ToArray();
    … …  
    280280            indices = Content.ProblemData.TestIndices.ToArray();
    281281            mean = Content.EstimatedTestValues.ToArray();
    282             s2 = Content.EstimatedTestVariance.ToArray();
     282            s2 = Content.EstimatedTestVariances.ToArray();
    283283            lower = mean.Zip(s2, GetLowerConfBound).ToArray();
    284284            upper = mean.Zip(s2, GetUpperConfBound).ToArray();
Note: See TracChangeset for help on using the changeset viewer.