Changeset 8664 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationModel.cs

Timestamp:

09/17/12 11:18:40 (12 years ago)

Author:

mkommend

Message:

#1951:

• Added linear scaling parameter to data analysis problems.
• Adapted interfaces, evaluators and analyzers accordingly.
• Added OnlineBoundedMeanSquaredErrorCalculator.
• Adapted symbolic regression sample unit test.

File:

• trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationModel.cs (modified) (1 diff)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationModel.cs

@@ -62 +62 @@
       return CreateClassificationSolution(problemData);
     }
-
-    #region scaling
-    public static void Scale(ISymbolicClassificationModel model, IClassificationProblemData problemData) {
-      var dataset = problemData.Dataset;
-      var targetVariable = problemData.TargetVariable;
-      var rows = problemData.TrainingIndices;
-      var estimatedValues = model.Interpreter.GetSymbolicExpressionTreeValues(model.SymbolicExpressionTree, dataset, rows);
-      var targetValues = dataset.GetDoubleValues(targetVariable, rows);
-      double alpha;
-      double beta;
-      OnlineCalculatorError errorState;
-      OnlineLinearScalingParameterCalculator.Calculate(estimatedValues, targetValues, out alpha, out beta, out errorState);
-      if (errorState != OnlineCalculatorError.None) return;
-
-      ConstantTreeNode alphaTreeNode = null;
-      ConstantTreeNode betaTreeNode = null;
-      // check if model has been scaled previously by analyzing the structure of the tree
-      var startNode = model.SymbolicExpressionTree.Root.GetSubtree(0);
-      if (startNode.GetSubtree(0).Symbol is Addition) {
-        var addNode = startNode.GetSubtree(0);
-        if (addNode.SubtreeCount == 2 && addNode.GetSubtree(0).Symbol is Multiplication && addNode.GetSubtree(1).Symbol is Constant) {
-          alphaTreeNode = addNode.GetSubtree(1) as ConstantTreeNode;
-          var mulNode = addNode.GetSubtree(0);
-          if (mulNode.SubtreeCount == 2 && mulNode.GetSubtree(1).Symbol is Constant) {
-            betaTreeNode = mulNode.GetSubtree(1) as ConstantTreeNode;
-          }
-        }
-      }
-      // if tree structure matches the structure necessary for linear scaling then reuse the existing tree nodes
-      if (alphaTreeNode != null && betaTreeNode != null) {
-        betaTreeNode.Value *= beta;
-        alphaTreeNode.Value *= beta;
-        alphaTreeNode.Value += alpha;
-      } else {
-        var mainBranch = startNode.GetSubtree(0);
-        startNode.RemoveSubtree(0);
-        var scaledMainBranch = MakeSum(MakeProduct(mainBranch, beta), alpha);
-        startNode.AddSubtree(scaledMainBranch);
-      }
-    }
-
-    private static ISymbolicExpressionTreeNode MakeSum(ISymbolicExpressionTreeNode treeNode, double alpha) {
-      if (alpha.IsAlmost(0.0)) {
-        return treeNode;
-      } else {
-        var addition = new Addition();
-        var node = addition.CreateTreeNode();
-        var alphaConst = MakeConstant(alpha);
-        node.AddSubtree(treeNode);
-        node.AddSubtree(alphaConst);
-        return node;
-      }
-    }
-
-    private static ISymbolicExpressionTreeNode MakeProduct(ISymbolicExpressionTreeNode treeNode, double beta) {
-      if (beta.IsAlmost(1.0)) {
-        return treeNode;
-      } else {
-        var multipliciation = new Multiplication();
-        var node = multipliciation.CreateTreeNode();
-        var betaConst = MakeConstant(beta);
-        node.AddSubtree(treeNode);
-        node.AddSubtree(betaConst);
-        return node;
-      }
-    }
-
-    private static ISymbolicExpressionTreeNode MakeConstant(double c) {
-      var node = (ConstantTreeNode)(new Constant()).CreateTreeNode();
-      node.Value = c;
-      return node;
-    }
-    #endregion
   }
 }