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Changeset 9919


Ignore:
Timestamp:
08/30/13 21:11:48 (11 years ago)
Author:
gkronber
Message:

#2101: fixed strings in classes for ANNs

Location:
trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork
Files:
3 edited

Legend:

Unmodified
Added
Removed
  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkClassification.cs

    r9456 r9919  
    2626using HeuristicLab.Core;
    2727using HeuristicLab.Data;
    28 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
    2928using HeuristicLab.Optimization;
     29using HeuristicLab.Parameters;
    3030using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
    3131using HeuristicLab.Problems.DataAnalysis;
    32 using HeuristicLab.Problems.DataAnalysis.Symbolic;
    33 using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
    34 using HeuristicLab.Parameters;
    3532
    3633namespace HeuristicLab.Algorithms.DataAnalysis {
     
    4744    private const string NodesInSecondHiddenLayerParameterName = "NodesInSecondHiddenLayer";
    4845    private const string RestartsParameterName = "Restarts";
    49     private const string NeuralNetworkRegressionModelResultName = "Neural network classification solution";
     46    private const string NeuralNetworkClassificationModelResultName = "Neural network classification solution";
    5047
    5148    #region parameter properties
     
    174171      double rmsError, avgRelError, relClassError;
    175172      var solution = CreateNeuralNetworkClassificationSolution(Problem.ProblemData, HiddenLayers, NodesInFirstHiddenLayer, NodesInSecondHiddenLayer, Decay, Restarts, out rmsError, out avgRelError, out relClassError);
    176       Results.Add(new Result(NeuralNetworkRegressionModelResultName, "The neural network regression solution.", solution));
    177       Results.Add(new Result("Root mean square error", "The root of the mean of squared errors of the neural network regression solution on the training set.", new DoubleValue(rmsError)));
    178       Results.Add(new Result("Average relative error", "The average of relative errors of the neural network regression solution on the training set.", new PercentValue(avgRelError)));
     173      Results.Add(new Result(NeuralNetworkClassificationModelResultName, "The neural network classification solution.", solution));
     174      Results.Add(new Result("Root mean square error", "The root of the mean of squared errors of the neural network classification solution on the training set.", new DoubleValue(rmsError)));
     175      Results.Add(new Result("Average relative error", "The average of relative errors of the neural network classification solution on the training set.", new PercentValue(avgRelError)));
    179176      Results.Add(new Result("Relative classification error", "The percentage of misclassified samples.", new PercentValue(relClassError)));
    180177    }
  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleClassification.cs

    r9456 r9919  
    2626using HeuristicLab.Core;
    2727using HeuristicLab.Data;
    28 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
    2928using HeuristicLab.Optimization;
     29using HeuristicLab.Parameters;
    3030using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
    3131using HeuristicLab.Problems.DataAnalysis;
    32 using HeuristicLab.Problems.DataAnalysis.Symbolic;
    33 using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
    34 using HeuristicLab.Parameters;
    3532
    3633namespace HeuristicLab.Algorithms.DataAnalysis {
     
    161158      var solution = CreateNeuralNetworkEnsembleClassificationSolution(Problem.ProblemData, EnsembleSize, HiddenLayers, NodesInFirstHiddenLayer, NodesInSecondHiddenLayer, Decay, Restarts, out rmsError, out avgRelError, out relClassError);
    162159      Results.Add(new Result(NeuralNetworkEnsembleClassificationModelResultName, "The neural network ensemble classification solution.", solution));
    163       Results.Add(new Result("Root mean square error", "The root of the mean of squared errors of the neural network ensemble regression solution on the training set.", new DoubleValue(rmsError)));
    164       Results.Add(new Result("Average relative error", "The average of relative errors of the neural network ensemble regression solution on the training set.", new PercentValue(avgRelError)));
     160      Results.Add(new Result("Root mean square error", "The root of the mean of squared errors of the neural network ensemble classification solution on the training set.", new DoubleValue(rmsError)));
     161      Results.Add(new Result("Average relative error", "The average of relative errors of the neural network ensemble classification solution on the training set.", new PercentValue(avgRelError)));
    165162      Results.Add(new Result("Relative classification error", "The percentage of misclassified samples.", new PercentValue(relClassError)));
    166163    }
     
    201198      int info;
    202199      alglib.mlpetraines(mlpEnsemble, inputMatrix, nRows, decay, restarts, out info, out rep);
    203       if (info != 6) throw new ArgumentException("Error in calculation of neural network ensemble regression solution");
     200      if (info != 6) throw new ArgumentException("Error in calculation of neural network ensemble classification solution");
    204201
    205202      rmsError = alglib.mlpermserror(mlpEnsemble, inputMatrix, nRows);
  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleRegression.cs

    r9456 r9919  
    2626using HeuristicLab.Core;
    2727using HeuristicLab.Data;
    28 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
    2928using HeuristicLab.Optimization;
     29using HeuristicLab.Parameters;
    3030using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
    3131using HeuristicLab.Problems.DataAnalysis;
    32 using HeuristicLab.Problems.DataAnalysis.Symbolic;
    33 using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
    34 using HeuristicLab.Parameters;
    3532
    3633namespace HeuristicLab.Algorithms.DataAnalysis {
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