Changeset 14869 for branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour

Timestamp:

04/14/17 08:58:45 (8 years ago)

Author:

gkronber

Message:

#2699: merged changesets from trunk to branch

Location:

branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4

Files:

• . (modified) (1 prop)
• NearestNeighbour/NearestNeighbourClassification.cs (modified) (2 diffs)
• NearestNeighbour/NearestNeighbourModel.cs (modified) (5 diffs)
• NearestNeighbour/NearestNeighbourRegression.cs (modified) (2 diffs)

branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour/NearestNeighbourClassification.cs

@@ -22 +22 @@
 using System;
 using System.Linq;
+using System.Threading;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -91 +92 @@
 
     #region nearest neighbour
-    protected override void Run() {
+    protected override void Run(CancellationToken cancellationToken) {
       double[] weights = null;
       if (Weights != null) weights = Weights.CloneAsArray();

branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour/NearestNeighbourModel.cs

@@ -119 +119 @@
       if (IsCompatibilityLoaded) {
         // no scaling
-        inputMatrix = AlglibUtil.PrepareInputMatrix(dataset,
+        inputMatrix = dataset.ToArray(
           this.allowedInputVariables.Concat(new string[] { targetVariable }),
           rows);
@@ -144 +144 @@
       if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x)))
         throw new NotSupportedException(
-          "Nearest neighbour classification does not support NaN or infinity values in the input dataset.");
+          "Nearest neighbour model does not support NaN or infinity values in the input dataset.");
 
       this.kdTree = new alglib.nearestneighbor.kdtree();
@@ -167 +167 @@
 
     private static double[,] CreateScaledData(IDataset dataset, IEnumerable<string> variables, IEnumerable<int> rows, double[] offsets, double[] factors) {
-      var x = new double[rows.Count(), variables.Count()];
-      var colIdx = 0;
-      foreach (var variableName in variables) {
-        var rowIdx = 0;
-        foreach (var val in dataset.GetDoubleValues(variableName, rows)) {
-          x[rowIdx, colIdx] = (val + offsets[colIdx]) * factors[colIdx];
-          rowIdx++;
-        }
-        colIdx++;
-      }
-      return x;
+      var transforms =
+        variables.Select(
+          (_, colIdx) =>
+            new LinearTransformation(variables) { Addend = offsets[colIdx] * factors[colIdx], Multiplier = factors[colIdx] });
+      return dataset.ToArray(variables, transforms, rows);
     }
 
@@ -187 +181 @@
       double[,] inputData;
       if (IsCompatibilityLoaded) {
-        inputData = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables, rows);
+        inputData = dataset.ToArray(allowedInputVariables, rows);
       } else {
         inputData = CreateScaledData(dataset, allowedInputVariables, rows, offsets, weights);
@@ -223 +217 @@
       double[,] inputData;
       if (IsCompatibilityLoaded) {
-        inputData = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables, rows);
+        inputData = dataset.ToArray(allowedInputVariables, rows);
       } else {
         inputData = CreateScaledData(dataset, allowedInputVariables, rows, offsets, weights);

branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour/NearestNeighbourRegression.cs

@@ -21 +21 @@
 
 using System;
+using System.Threading;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -92 +93 @@
 
     #region nearest neighbour
-    protected override void Run() {
+    protected override void Run(CancellationToken cancellationToken) {
       double[] weights = null;
       if (Weights != null) weights = Weights.CloneAsArray();