- Timestamp:
- 07/06/17 11:12:18 (7 years ago)
- Location:
- stable/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork
- Files:
-
- 6 edited
Legend:
- Unmodified
- Added
- Removed
-
stable/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkClassification.cs
r15061 r15142 184 184 IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables; 185 185 IEnumerable<int> rows = problemData.TrainingIndices; 186 double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(dataset,allowedInputVariables.Concat(new string[] { targetVariable }), rows);186 double[,] inputMatrix = dataset.ToArray(allowedInputVariables.Concat(new string[] { targetVariable }), rows); 187 187 if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x))) 188 188 throw new NotSupportedException("Neural network classification does not support NaN or infinity values in the input dataset."); -
stable/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleClassification.cs
r15061 r15142 125 125 public NeuralNetworkEnsembleClassification() 126 126 : base() { 127 var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] { 128 (IntValue)new IntValue(0).AsReadOnly(), 129 (IntValue)new IntValue(1).AsReadOnly(), 127 var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] { 128 (IntValue)new IntValue(0).AsReadOnly(), 129 (IntValue)new IntValue(1).AsReadOnly(), 130 130 (IntValue)new IntValue(2).AsReadOnly() }); 131 131 var selectedHiddenLayerValue = (from v in validHiddenLayerValues … … 170 170 IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables; 171 171 IEnumerable<int> rows = problemData.TrainingIndices; 172 double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(dataset,allowedInputVariables.Concat(new string[] { targetVariable }), rows);172 double[,] inputMatrix = dataset.ToArray(allowedInputVariables.Concat(new string[] { targetVariable }), rows); 173 173 if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x))) 174 174 throw new NotSupportedException("Neural network ensemble classification does not support NaN or infinity values in the input dataset."); -
stable/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleModel.cs
r14186 r15142 91 91 92 92 public IEnumerable<double> GetEstimatedValues(IDataset dataset, IEnumerable<int> rows) { 93 double[,] inputData = AlglibUtil.PrepareInputMatrix(dataset,allowedInputVariables, rows);93 double[,] inputData = dataset.ToArray(allowedInputVariables, rows); 94 94 95 95 int n = inputData.GetLength(0); … … 108 108 109 109 public override IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) { 110 double[,] inputData = AlglibUtil.PrepareInputMatrix(dataset,allowedInputVariables, rows);110 double[,] inputData = dataset.ToArray(allowedInputVariables, rows); 111 111 112 112 int n = inputData.GetLength(0); -
stable/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleRegression.cs
r15061 r15142 169 169 IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables; 170 170 IEnumerable<int> rows = problemData.TrainingIndices; 171 double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(dataset,allowedInputVariables.Concat(new string[] { targetVariable }), rows);171 double[,] inputMatrix = dataset.ToArray(allowedInputVariables.Concat(new string[] { targetVariable }), rows); 172 172 if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x))) 173 173 throw new NotSupportedException("Neural network ensemble regression does not support NaN or infinity values in the input dataset."); -
stable/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkModel.cs
r14186 r15142 95 95 96 96 public IEnumerable<double> GetEstimatedValues(IDataset dataset, IEnumerable<int> rows) { 97 double[,] inputData = AlglibUtil.PrepareInputMatrix(dataset,allowedInputVariables, rows);97 double[,] inputData = dataset.ToArray(allowedInputVariables, rows); 98 98 99 99 int n = inputData.GetLength(0); … … 112 112 113 113 public override IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) { 114 double[,] inputData = AlglibUtil.PrepareInputMatrix(dataset,allowedInputVariables, rows);114 double[,] inputData = dataset.ToArray( allowedInputVariables, rows); 115 115 116 116 int n = inputData.GetLength(0); -
stable/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkRegression.cs
r15061 r15142 185 185 IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables; 186 186 IEnumerable<int> rows = problemData.TrainingIndices; 187 double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(dataset,allowedInputVariables.Concat(new string[] { targetVariable }), rows);187 double[,] inputMatrix = dataset.ToArray(allowedInputVariables.Concat(new string[] { targetVariable }), rows); 188 188 if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x))) 189 189 throw new NotSupportedException("Neural network regression does not support NaN or infinity values in the input dataset.");
Note: See TracChangeset
for help on using the changeset viewer.