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Ignore:
Timestamp:
08/08/12 14:04:17 (12 years ago)
Author:
mkommend
Message:

#1081: Intermediate commit of trunk updates - interpreter changes must be redone.

Location:
branches/HeuristicLab.TimeSeries
Files:
7 edited

Legend:

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  • branches/HeuristicLab.TimeSeries

    • Property svn:ignore

      •  

        old new  
        2020bin
        2121protoc.exe
         22_ReSharper.HeuristicLab.TimeSeries-3.3

  • branches/HeuristicLab.TimeSeries/HeuristicLab.Algorithms.DataAnalysis

  • branches/HeuristicLab.TimeSeries/HeuristicLab.Algorithms.DataAnalysis/3.4

    • Property svn:ignore

      •  

        old new  
        55*.vs10x
        66Plugin.cs
         7*.user

  • branches/HeuristicLab.TimeSeries/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkClassification.cs

    r7259 r8430  
    5353      get { return (IFixedValueParameter<DoubleValue>)Parameters[DecayParameterName]; }
    5454    }
    55     public ConstrainedValueParameter<IntValue> HiddenLayersParameter {
    56       get { return (ConstrainedValueParameter<IntValue>)Parameters[HiddenLayersParameterName]; }
     55    public IConstrainedValueParameter<IntValue> HiddenLayersParameter {
     56      get { return (IConstrainedValueParameter<IntValue>)Parameters[HiddenLayersParameterName]; }
    5757    }
    5858    public IFixedValueParameter<IntValue> NodesInFirstHiddenLayerParameter {
    … …  
    185185      string targetVariable = problemData.TargetVariable;
    186186      IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables;
    187       IEnumerable<int> rows = problemData.TrainingIndizes;
     187      IEnumerable<int> rows = problemData.TrainingIndices;
    188188      double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables.Concat(new string[] { targetVariable }), rows);
    189189      if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x)))
    … …  
    195195      int nClasses = classValues.Count();
    196196      // map original class values to values [0..nClasses-1]
    197       Dictionary<double, double> classIndizes = new Dictionary<double, double>();
     197      Dictionary<double, double> classIndices = new Dictionary<double, double>();
    198198      for (int i = 0; i < nClasses; i++) {
    199         classIndizes[classValues[i]] = i;
     199        classIndices[classValues[i]] = i;
    200200      }
    201201      for (int row = 0; row < nRows; row++) {
    202         inputMatrix[row, nFeatures] = classIndizes[inputMatrix[row, nFeatures]];
     202        inputMatrix[row, nFeatures] = classIndices[inputMatrix[row, nFeatures]];
    203203      }
    204204

  • branches/HeuristicLab.TimeSeries/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleClassification.cs

    r7259 r8430  
    5757      get { return (IFixedValueParameter<DoubleValue>)Parameters[DecayParameterName]; }
    5858    }
    59     public ConstrainedValueParameter<IntValue> HiddenLayersParameter {
    60       get { return (ConstrainedValueParameter<IntValue>)Parameters[HiddenLayersParameterName]; }
     59    public IConstrainedValueParameter<IntValue> HiddenLayersParameter {
     60      get { return (IConstrainedValueParameter<IntValue>)Parameters[HiddenLayersParameterName]; }
    6161    }
    6262    public IFixedValueParameter<IntValue> NodesInFirstHiddenLayerParameter {
    … …  
    171171      string targetVariable = problemData.TargetVariable;
    172172      IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables;
    173       IEnumerable<int> rows = problemData.TrainingIndizes;
     173      IEnumerable<int> rows = problemData.TrainingIndices;
    174174      double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables.Concat(new string[] { targetVariable }), rows);
    175175      if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x)))
    … …  
    181181      int nClasses = classValues.Count();
    182182      // map original class values to values [0..nClasses-1]
    183       Dictionary<double, double> classIndizes = new Dictionary<double, double>();
     183      Dictionary<double, double> classIndices = new Dictionary<double, double>();
    184184      for (int i = 0; i < nClasses; i++) {
    185         classIndizes[classValues[i]] = i;
     185        classIndices[classValues[i]] = i;
    186186      }
    187187      for (int row = 0; row < nRows; row++) {
    188         inputMatrix[row, nFeatures] = classIndizes[inputMatrix[row, nFeatures]];
     188        inputMatrix[row, nFeatures] = classIndices[inputMatrix[row, nFeatures]];
    189189      }
    190190

  • branches/HeuristicLab.TimeSeries/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleRegression.cs

    r7259 r8430  
    5757      get { return (IFixedValueParameter<DoubleValue>)Parameters[DecayParameterName]; }
    5858    }
    59     public ConstrainedValueParameter<IntValue> HiddenLayersParameter {
    60       get { return (ConstrainedValueParameter<IntValue>)Parameters[HiddenLayersParameterName]; }
     59    public IConstrainedValueParameter<IntValue> HiddenLayersParameter {
     60      get { return (IConstrainedValueParameter<IntValue>)Parameters[HiddenLayersParameterName]; }
    6161    }
    6262    public IFixedValueParameter<IntValue> NodesInFirstHiddenLayerParameter {
    … …  
    170170      string targetVariable = problemData.TargetVariable;
    171171      IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables;
    172       IEnumerable<int> rows = problemData.TrainingIndizes;
     172      IEnumerable<int> rows = problemData.TrainingIndices;
    173173      double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables.Concat(new string[] { targetVariable }), rows);
    174174      if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x)))

  • branches/HeuristicLab.TimeSeries/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkRegression.cs

    r7259 r8430  
    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 {
    … …  
    5350      get { return (IFixedValueParameter<DoubleValue>)Parameters[DecayParameterName]; }
    5451    }
    55     public ConstrainedValueParameter<IntValue> HiddenLayersParameter {
    56       get { return (ConstrainedValueParameter<IntValue>)Parameters[HiddenLayersParameterName]; }
     52    public IConstrainedValueParameter<IntValue> HiddenLayersParameter {
     53      get { return (IConstrainedValueParameter<IntValue>)Parameters[HiddenLayersParameterName]; }
    5754    }
    5855    public IFixedValueParameter<IntValue> NodesInFirstHiddenLayerParameter {
    … …  
    186183      string targetVariable = problemData.TargetVariable;
    187184      IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables;
    188       IEnumerable<int> rows = problemData.TrainingIndizes;
     185      IEnumerable<int> rows = problemData.TrainingIndices;
    189186      double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables.Concat(new string[] { targetVariable }), rows);
    190187      if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x)))
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