Changeset 12696 for branches/GBT-trunkintegration/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesAlgorithmStatic.cs

Timestamp:

07/09/15 16:11:52 (9 years ago)

Author:

gkronber

Message:

#2261: killed all weights

File:

• branches/GBT-trunkintegration/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesAlgorithmStatic.cs (modified) (6 diffs)

branches/GBT-trunkintegration/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesAlgorithmStatic.cs

@@ -55 +55 @@
       internal double[] pred;
       internal double[] predTest;
-      internal double[] w;
       internal double[] y;
       internal int[] activeIdx;
@@ -77 +76 @@
 
         y = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, problemData.TrainingIndices).ToArray();
-        // weights are all 1 for now (HL doesn't support weights yet)
-        w = Enumerable.Repeat(1.0, nRows).ToArray();
 
         treeBuilder = new RegressionTreeBuilder(problemData, random);
@@ -85 +82 @@
 
         var zeros = Enumerable.Repeat(0.0, nRows);
-        var ones = Enumerable.Repeat(1.0, nRows);
-        double f0 = lossFunction.GetLineSearchFunc(y, zeros, ones)(activeIdx, 0, nRows - 1); // initial constant value (mean for squared errors)
+        double f0 = lossFunction.GetLineSearchFunc(y, zeros)(activeIdx, 0, nRows - 1); // initial constant value (mean for squared errors)
         pred = Enumerable.Repeat(f0, nRows).ToArray();
         predTest = Enumerable.Repeat(f0, problemData.TestIndices.Count()).ToArray();
@@ -107 +103 @@
       public double GetTrainLoss() {
         int nRows = y.Length;
-        return lossFunction.GetLoss(y, pred, w) / nRows;
+        return lossFunction.GetLoss(y, pred) / nRows;
       }
       public double GetTestLoss() {
         var yTest = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, problemData.TestIndices);
-        var wTest = problemData.TestIndices.Select(_ => 1.0); // ones
         var nRows = problemData.TestIndices.Count();
-        return lossFunction.GetLoss(yTest, predTest, wTest) / nRows;
+        return lossFunction.GetLoss(yTest, predTest) / nRows;
       }
     }
@@ -160 +155 @@
       var yPred = gbmState.pred;
       var yPredTest = gbmState.predTest;
-      var w = gbmState.w;
       var treeBuilder = gbmState.treeBuilder;
       var y = gbmState.y;
@@ -168 +162 @@
       // copy output of gradient function to pre-allocated rim array (pseudo-residuals)
       int rimIdx = 0;
-      foreach (var g in lossFunction.GetLossGradient(y, yPred, w)) {
+      foreach (var g in lossFunction.GetLossGradient(y, yPred)) {
         pseudoRes[rimIdx++] = g;
       }
 
-      var tree = treeBuilder.CreateRegressionTreeForGradientBoosting(pseudoRes, maxSize, activeIdx, lossFunction.GetLineSearchFunc(y, yPred, w), r, m);
+      var tree = treeBuilder.CreateRegressionTreeForGradientBoosting(pseudoRes, maxSize, activeIdx, lossFunction.GetLineSearchFunc(y, yPred), r, m);
 
       int i = 0;