Changeset 15783 for trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork

Timestamp:

02/16/18 11:35:54 (6 years ago)

Author:

fholzing

Message:

#2902: Changed from Cast to Iterator and adapted all occurrences.

Location:

trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork

Files:

• NeuralNetworkClassification.cs (modified) (2 diffs)
• NeuralNetworkEnsembleClassification.cs (modified) (1 diff)
• NeuralNetworkEnsembleRegression.cs (modified) (2 diffs)
• NeuralNetworkRegression.cs (modified) (2 diffs)

trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkClassification.cs

@@ -115 +115 @@
     public NeuralNetworkClassification()
       : base() {
-      var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] { 
-        (IntValue)new IntValue(0).AsReadOnly(), 
-        (IntValue)new IntValue(1).AsReadOnly(), 
+      var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] {
+        (IntValue)new IntValue(0).AsReadOnly(),
+        (IntValue)new IntValue(1).AsReadOnly(),
         (IntValue)new IntValue(2).AsReadOnly() });
       var selectedHiddenLayerValue = (from v in validHiddenLayerValues
@@ -185 +185 @@
       IEnumerable<int> rows = problemData.TrainingIndices;
       double[,] inputMatrix = dataset.ToArray(allowedInputVariables.Concat(new string[] { targetVariable }), rows);
-      if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x)))
+      if (inputMatrix.ContainsNanInf())
         throw new NotSupportedException("Neural network classification does not support NaN or infinity values in the input dataset.");
 

trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleClassification.cs

@@ -171 +171 @@
       IEnumerable<int> rows = problemData.TrainingIndices;
       double[,] inputMatrix = dataset.ToArray(allowedInputVariables.Concat(new string[] { targetVariable }), rows);
-      if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x)))
+      if (inputMatrix.ContainsNanInf())
         throw new NotSupportedException("Neural network ensemble classification does not support NaN or infinity values in the input dataset.");
 

trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleRegression.cs

@@ -125 +125 @@
     public NeuralNetworkEnsembleRegression()
       : base() {
-      var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] { 
-        (IntValue)new IntValue(0).AsReadOnly(), 
-        (IntValue)new IntValue(1).AsReadOnly(), 
+      var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] {
+        (IntValue)new IntValue(0).AsReadOnly(),
+        (IntValue)new IntValue(1).AsReadOnly(),
         (IntValue)new IntValue(2).AsReadOnly() });
       var selectedHiddenLayerValue = (from v in validHiddenLayerValues
@@ -170 +170 @@
       IEnumerable<int> rows = problemData.TrainingIndices;
       double[,] inputMatrix = dataset.ToArray(allowedInputVariables.Concat(new string[] { targetVariable }), rows);
-      if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x)))
+      if (inputMatrix.ContainsNanInf())
         throw new NotSupportedException("Neural network ensemble regression does not support NaN or infinity values in the input dataset.");
 

trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkRegression.cs

@@ -115 +115 @@
     public NeuralNetworkRegression()
       : base() {
-      var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] { 
-        (IntValue)new IntValue(0).AsReadOnly(), 
-        (IntValue)new IntValue(1).AsReadOnly(), 
+      var validHiddenLayerValues = new ItemSet<IntValue>(new IntValue[] {
+        (IntValue)new IntValue(0).AsReadOnly(),
+        (IntValue)new IntValue(1).AsReadOnly(),
         (IntValue)new IntValue(2).AsReadOnly() });
       var selectedHiddenLayerValue = (from v in validHiddenLayerValues
@@ -186 +186 @@
       IEnumerable<int> rows = problemData.TrainingIndices;
       double[,] inputMatrix = dataset.ToArray(allowedInputVariables.Concat(new string[] { targetVariable }), rows);
-      if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x)))
+      if (inputMatrix.ContainsNanInf())
         throw new NotSupportedException("Neural network regression does not support NaN or infinity values in the input dataset.");