Changeset 16892 for branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis/3.4
- Timestamp:
- 05/04/19 08:22:42 (5 years ago)
- Location:
- branches/2925_AutoDiffForDynamicalModels
- Files:
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- 10 edited
- 1 copied
Legend:
- Unmodified
- Added
- Removed
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branches/2925_AutoDiffForDynamicalModels
- Property svn:mergeinfo changed
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branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis
- Property svn:mergeinfo changed
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branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis/3.4
- Property svn:mergeinfo changed
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branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis/3.4/CrossValidation.cs
r16662 r16892 300 300 if ((ExecutionState != ExecutionState.Prepared) && (ExecutionState != ExecutionState.Paused)) 301 301 throw new InvalidOperationException(string.Format("Start not allowed in execution state \"{0}\".", ExecutionState)); 302 seed = new FastRandom().NextInt();302 seed = RandomSeedGenerator.GetSeed(); 303 303 304 304 if (Algorithm == null) return; -
branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/RegressionTreeModel.cs
r16662 r16892 91 91 #region old storable format 92 92 // remove with HL 3.4 93 [Storable( AllowOneWay = true)]93 [Storable(OldName = "SerializedTree")] 94 94 // to prevent storing the references to data caches in nodes 95 95 // seemingly, it is bad (performance-wise) to persist tuples (tuples are used as keys in a dictionary) -
branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour/NearestNeighbourModel.cs
r16662 r16892 294 294 return IsProblemDataCompatible(classificationProblemData, out errorMessage); 295 295 296 throw new ArgumentException("The problem data is not a regression nor a classification problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");296 throw new ArgumentException("The problem data is not compatible with this nearest neighbour model. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData"); 297 297 } 298 298 -
branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleModel.cs
r16662 r16892 144 144 return IsProblemDataCompatible(classificationProblemData, out errorMessage); 145 145 146 throw new ArgumentException("The problem data is not a regression nor a classification problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");146 throw new ArgumentException("The problem data is not compatible with this neural network ensemble. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData"); 147 147 } 148 148 … … 153 153 return new NeuralNetworkEnsembleClassificationSolution(this, new ClassificationEnsembleProblemData(problemData)); 154 154 } 155 155 156 156 #region persistence 157 157 [Storable] … … 183 183 } 184 184 } 185 [Storable( AllowOneWay = true)]185 [Storable(OldName = "MultiLayerPerceptronEnsembleDfdnet")] 186 186 private double[] MultiLayerPerceptronEnsembleDfdnet { 187 187 set { … … 197 197 } 198 198 } 199 [Storable( AllowOneWay = true)]199 [Storable(OldName = "MultiLayerPerceptronEnsembleNeurons")] 200 200 private double[] MultiLayerPerceptronEnsembleNeurons { 201 201 set { mlpEnsemble.innerobj.network.neurons = value; } 202 202 } 203 [Storable( AllowOneWay = true)]203 [Storable(OldName = "MultiLayerPerceptronEnsembleSerializedMlp")] 204 204 private double[] MultiLayerPerceptronEnsembleSerializedMlp { 205 205 set { … … 207 207 } 208 208 } 209 [Storable( AllowOneWay = true)]209 [Storable(OldName = "MultiLayerPerceptronStuctinfo")] 210 210 private int[] MultiLayerPerceptronStuctinfo { 211 211 set { -
branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkModel.cs
r16662 r16892 147 147 return IsProblemDataCompatible(classificationProblemData, out errorMessage); 148 148 149 throw new ArgumentException("The problem data is not a regression nor a classification problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");149 throw new ArgumentException("The problem data is not compatible with this neural network. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData"); 150 150 } 151 151 -
branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis/3.4/RandomForest/RandomForestModel.cs
r16662 r16892 300 300 return IsProblemDataCompatible(classificationProblemData, out errorMessage); 301 301 302 throw new ArgumentException("The problem data is not a regression nor a classification problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");302 throw new ArgumentException("The problem data is not compatible with this random forest. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData"); 303 303 } 304 304 -
branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis/3.4/SupportVectorMachine/SupportVectorMachineModel.cs
r16662 r16892 143 143 return IsProblemDataCompatible(classificationProblemData, out errorMessage); 144 144 145 throw new ArgumentException("The problem data is not a regression nor a classification problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");145 throw new ArgumentException("The problem data is not compatible with this SVM. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData"); 146 146 } 147 147
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