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Timestamp:
10/16/12 09:44:07 (12 years ago)
Author:
sforsten
Message:

#1776:

Location:
branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis
Files:
6 edited

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  • branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis

  • branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/ConstantRegressionModel.cs

    r8534 r8811  
    3030  public class ConstantRegressionModel : NamedItem, IRegressionModel {
    3131    [Storable]
    32     private double constant;
     32    protected double constant;
    3333    public double Constant {
    3434      get { return constant; }

  • branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionEnsembleSolution.cs

    r8508 r8811  
    3636  [Item("Regression Ensemble Solution", "A regression solution that contains an ensemble of multiple regression models")]
    3737  [Creatable("Data Analysis - Ensembles")]
    38   public sealed class RegressionEnsembleSolution : RegressionSolution, IRegressionEnsembleSolution {
     38  public sealed class RegressionEnsembleSolution : RegressionSolutionBase, IRegressionEnsembleSolution {
    3939    private readonly Dictionary<int, double> trainingEvaluationCache = new Dictionary<int, double>();
    4040    private readonly Dictionary<int, double> testEvaluationCache = new Dictionary<int, double>();
     41    private readonly Dictionary<int, double> evaluationCache = new Dictionary<int, double>();
    4142
    4243    public new IRegressionEnsembleModel Model {
    … …  
    155156    }
    156157
    157     protected override void RecalculateResults() {
    158       CalculateResults();
    159     }
    160 
    161158    #region Evaluation
     159    public override IEnumerable<double> EstimatedValues {
     160      get { return GetEstimatedValues(Enumerable.Range(0, ProblemData.Dataset.Rows)); }
     161    }
     162
    162163    public override IEnumerable<double> EstimatedTrainingValues {
    163164      get {

  • branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionProblem.cs

    r7866 r8811  
    3636    public override IDeepCloneable Clone(Cloner cloner) { return new RegressionProblem(this, cloner); }
    3737
    38     public RegressionProblem()
    39       : base() {
    40       ProblemData = new RegressionProblemData();
    41     }
     38    public RegressionProblem() : base(new RegressionProblemData()) { }
     39
    4240  }
    4341}

  • branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionSolution.cs

    r8508 r8811  
    4545      : base(model, problemData) {
    4646      evaluationCache = new Dictionary<int, double>(problemData.Dataset.Rows);
     47      CalculateRegressionResults();
    4748    }
    4849
    49     protected override void RecalculateResults() {
    50       CalculateResults();
    51     }
    5250
    5351    public override IEnumerable<double> EstimatedValues {

  • branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionSolutionBase.cs

    r8508 r8811  
    2929  [StorableClass]
    3030  public abstract class RegressionSolutionBase : DataAnalysisSolution, IRegressionSolution {
    31     private const string TrainingMeanSquaredErrorResultName = "Mean squared error (training)";
    32     private const string TestMeanSquaredErrorResultName = "Mean squared error (test)";
    33     private const string TrainingMeanAbsoluteErrorResultName = "Mean absolute error (training)";
    34     private const string TestMeanAbsoluteErrorResultName = "Mean absolute error (test)";
    35     private const string TrainingSquaredCorrelationResultName = "Pearson's R² (training)";
    36     private const string TestSquaredCorrelationResultName = "Pearson's R² (test)";
    37     private const string TrainingRelativeErrorResultName = "Average relative error (training)";
    38     private const string TestRelativeErrorResultName = "Average relative error (test)";
    39     private const string TrainingNormalizedMeanSquaredErrorResultName = "Normalized mean squared error (training)";
    40     private const string TestNormalizedMeanSquaredErrorResultName = "Normalized mean squared error (test)";
    41     private const string TrainingMeanErrorResultName = "Mean error (training)";
    42     private const string TestMeanErrorResultName = "Mean error (test)";
     31    protected const string TrainingMeanSquaredErrorResultName = "Mean squared error (training)";
     32    protected const string TestMeanSquaredErrorResultName = "Mean squared error (test)";
     33    protected const string TrainingMeanAbsoluteErrorResultName = "Mean absolute error (training)";
     34    protected const string TestMeanAbsoluteErrorResultName = "Mean absolute error (test)";
     35    protected const string TrainingSquaredCorrelationResultName = "Pearson's R² (training)";
     36    protected const string TestSquaredCorrelationResultName = "Pearson's R² (test)";
     37    protected const string TrainingRelativeErrorResultName = "Average relative error (training)";
     38    protected const string TestRelativeErrorResultName = "Average relative error (test)";
     39    protected const string TrainingNormalizedMeanSquaredErrorResultName = "Normalized mean squared error (training)";
     40    protected const string TestNormalizedMeanSquaredErrorResultName = "Normalized mean squared error (test)";
     41    protected const string TrainingMeanErrorResultName = "Mean error (training)";
     42    protected const string TestMeanErrorResultName = "Mean error (test)";
     43
     44    protected const string TrainingMeanSquaredErrorResultDescription = "Mean of squared errors of the model on the training partition";
     45    protected const string TestMeanSquaredErrorResultDescription = "Mean of squared errors of the model on the test partition";
     46    protected const string TrainingMeanAbsoluteErrorResultDescription = "Mean of absolute errors of the model on the training partition";
     47    protected const string TestMeanAbsoluteErrorResultDescription = "Mean of absolute errors of the model on the test partition";
     48    protected const string TrainingSquaredCorrelationResultDescription = "Squared Pearson's correlation coefficient of the model output and the actual values on the training partition";
     49    protected const string TestSquaredCorrelationResultDescription = "Squared Pearson's correlation coefficient of the model output and the actual values on the test partition";
     50    protected const string TrainingRelativeErrorResultDescription = "Average of the relative errors of the model output and the actual values on the training partition";
     51    protected const string TestRelativeErrorResultDescription = "Average of the relative errors of the model output and the actual values on the test partition";
     52    protected const string TrainingNormalizedMeanSquaredErrorResultDescription = "Normalized mean of squared errors of the model on the training partition";
     53    protected const string TestNormalizedMeanSquaredErrorResultDescription = "Normalized mean of squared errors of the model on the test partition";
     54    protected const string TrainingMeanErrorResultDescription = "Mean of errors of the model on the training partition";
     55    protected const string TestMeanErrorResultDescription = "Mean of errors of the model on the test partition";
    4356
    4457    public new IRegressionModel Model {
    … …  
    115128    protected RegressionSolutionBase(IRegressionModel model, IRegressionProblemData problemData)
    116129      : base(model, problemData) {
    117       Add(new Result(TrainingMeanSquaredErrorResultName, "Mean of squared errors of the model on the training partition", new DoubleValue()));
    118       Add(new Result(TestMeanSquaredErrorResultName, "Mean of squared errors of the model on the test partition", new DoubleValue()));
    119       Add(new Result(TrainingMeanAbsoluteErrorResultName, "Mean of absolute errors of the model on the training partition", new DoubleValue()));
    120       Add(new Result(TestMeanAbsoluteErrorResultName, "Mean of absolute errors of the model on the test partition", new DoubleValue()));
    121       Add(new Result(TrainingSquaredCorrelationResultName, "Squared Pearson's correlation coefficient of the model output and the actual values on the training partition", new DoubleValue()));
    122       Add(new Result(TestSquaredCorrelationResultName, "Squared Pearson's correlation coefficient of the model output and the actual values on the test partition", new DoubleValue()));
    123       Add(new Result(TrainingRelativeErrorResultName, "Average of the relative errors of the model output and the actual values on the training partition", new PercentValue()));
    124       Add(new Result(TestRelativeErrorResultName, "Average of the relative errors of the model output and the actual values on the test partition", new PercentValue()));
    125       Add(new Result(TrainingNormalizedMeanSquaredErrorResultName, "Normalized mean of squared errors of the model on the training partition", new DoubleValue()));
    126       Add(new Result(TestNormalizedMeanSquaredErrorResultName, "Normalized mean of squared errors of the model on the test partition", new DoubleValue()));
    127       Add(new Result(TrainingMeanErrorResultName, "Mean of errors of the model on the training partition", new DoubleValue()));
    128       Add(new Result(TestMeanErrorResultName, "Mean of errors of the model on the test partition", new DoubleValue()));
     130      Add(new Result(TrainingMeanSquaredErrorResultName, TrainingMeanSquaredErrorResultDescription, new DoubleValue()));
     131      Add(new Result(TestMeanSquaredErrorResultName, TestMeanSquaredErrorResultDescription, new DoubleValue()));
     132      Add(new Result(TrainingMeanAbsoluteErrorResultName, TrainingMeanAbsoluteErrorResultDescription, new DoubleValue()));
     133      Add(new Result(TestMeanAbsoluteErrorResultName, TestMeanAbsoluteErrorResultDescription, new DoubleValue()));
     134      Add(new Result(TrainingSquaredCorrelationResultName, TrainingSquaredCorrelationResultDescription, new DoubleValue()));
     135      Add(new Result(TestSquaredCorrelationResultName, TestSquaredCorrelationResultDescription, new DoubleValue()));
     136      Add(new Result(TrainingRelativeErrorResultName, TrainingRelativeErrorResultDescription, new PercentValue()));
     137      Add(new Result(TestRelativeErrorResultName, TestRelativeErrorResultDescription, new PercentValue()));
     138      Add(new Result(TrainingNormalizedMeanSquaredErrorResultName, TrainingNormalizedMeanSquaredErrorResultDescription, new DoubleValue()));
     139      Add(new Result(TestNormalizedMeanSquaredErrorResultName, TestNormalizedMeanSquaredErrorResultDescription, new DoubleValue()));
     140      Add(new Result(TrainingMeanErrorResultName, TrainingMeanErrorResultDescription, new DoubleValue()));
     141      Add(new Result(TestMeanErrorResultName, TestMeanErrorResultDescription, new DoubleValue()));
    129142    }
    130143
    … …  
    164177    }
    165178
    166     protected void CalculateResults() {
     179    protected override void RecalculateResults() {
     180      CalculateRegressionResults();
     181    }
     182
     183    protected void CalculateRegressionResults() {
    167184      IEnumerable<double> estimatedTrainingValues = EstimatedTrainingValues; // cache values
    168185      IEnumerable<double> originalTrainingValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices);
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