Changeset 14029 for branches/crossvalidation-2434/HeuristicLab.Algorithms.DataAnalysis/3.4/Nca/NcaModel.cs
- Timestamp:
- 07/08/16 14:40:02 (8 years ago)
- Location:
- branches/crossvalidation-2434
- Files:
-
- 3 edited
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branches/crossvalidation-2434
- Property svn:mergeinfo changed
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branches/crossvalidation-2434/HeuristicLab.Algorithms.DataAnalysis
- Property svn:mergeinfo changed
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branches/crossvalidation-2434/HeuristicLab.Algorithms.DataAnalysis/3.4/Nca/NcaModel.cs
r12509 r14029 30 30 [Item("NCA Model", "")] 31 31 [StorableClass] 32 public class NcaModel : NamedItem, INcaModel { 32 public class NcaModel : ClassificationModel, INcaModel { 33 public override IEnumerable<string> VariablesUsedForPrediction { 34 get { return allowedInputVariables; } 35 } 33 36 34 37 [Storable] … … 39 42 [Storable] 40 43 private string[] allowedInputVariables; 41 [Storable]42 private string targetVariable;43 44 [Storable] 44 45 private INearestNeighbourModel nnModel; … … 52 53 this.transformationMatrix = (double[,])original.transformationMatrix.Clone(); 53 54 this.allowedInputVariables = (string[])original.allowedInputVariables.Clone(); 54 this.targetVariable = original.targetVariable;55 55 this.nnModel = cloner.Clone(original.nnModel); 56 56 this.classValues = (double[])original.classValues.Clone(); 57 57 } 58 public NcaModel(int k, double[,] transformationMatrix, IDataset dataset, IEnumerable<int> rows, string targetVariable, IEnumerable<string> allowedInputVariables, double[] classValues) { 58 public NcaModel(int k, double[,] transformationMatrix, IDataset dataset, IEnumerable<int> rows, string targetVariable, IEnumerable<string> allowedInputVariables, double[] classValues) 59 : base(targetVariable) { 59 60 Name = ItemName; 60 61 Description = ItemDescription; 61 62 this.transformationMatrix = (double[,])transformationMatrix.Clone(); 62 63 this.allowedInputVariables = allowedInputVariables.ToArray(); 63 this.targetVariable = targetVariable;64 64 this.classValues = (double[])classValues.Clone(); 65 65 … … 72 72 } 73 73 74 public IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) {74 public override IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) { 75 75 var ds = ReduceDataset(dataset, rows); 76 76 return nnModel.GetEstimatedClassValues(ds, Enumerable.Range(0, ds.Rows)); 77 77 } 78 78 79 public INcaClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData) {80 return new NcaClassificationSolution( new ClassificationProblemData(problemData), this);79 public override IClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData) { 80 return new NcaClassificationSolution(this, new ClassificationProblemData(problemData)); 81 81 } 82 82 83 I ClassificationSolution IClassificationModel.CreateClassificationSolution(IClassificationProblemData problemData) {84 return CreateClassificationSolution(problemData);83 INcaClassificationSolution INcaModel.CreateClassificationSolution(IClassificationProblemData problemData) { 84 return new NcaClassificationSolution(this, new ClassificationProblemData(problemData)); 85 85 } 86 86 … … 88 88 var data = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables, rows); 89 89 90 var targets = dataset.GetDoubleValues( targetVariable, rows).ToArray();90 var targets = dataset.GetDoubleValues(TargetVariable, rows).ToArray(); 91 91 var result = new double[data.GetLength(0), transformationMatrix.GetLength(1) + 1]; 92 92 for (int i = 0; i < data.GetLength(0); i++) … … 104 104 .Range(0, transformationMatrix.GetLength(1)) 105 105 .Select(x => "X" + x.ToString()) 106 .Concat( targetVariable.ToEnumerable()),106 .Concat(TargetVariable.ToEnumerable()), 107 107 Reduce(dataset, rows)); 108 108 }
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