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Ignore:
Timestamp:
10/21/16 17:59:36 (8 years ago)
Author:
gkronber
Message:

#2690: implemented methods to generate symbolic expression tree solutions for decision tree models (random forest and gradient boosted) as well as views which make it possible to inspect each of the individual trees in a GBT and RF solution

Location:
trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees
Files:
3 edited

Legend:

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  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesAlgorithm.cs

    r14185 r14345  
    269269        } else {
    270270          // otherwise we produce a regression solution
    271           Results.Add(new Result("Solution", new RegressionSolution(model, problemData)));
     271          Results.Add(new Result("Solution", new GradientBoostedTreesSolution(model, problemData)));
    272272        }
    273273      }
  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesSolution.cs

    r14185 r14345  
    2020#endregion
    2121
    22 using System.Collections.Generic;
    23 using System.Linq;
    2422using HeuristicLab.Common;
    2523using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/RegressionTreeModel.cs

    r14185 r14345  
    2828using HeuristicLab.Common;
    2929using HeuristicLab.Core;
     30using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
    3031using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
    3132using HeuristicLab.Problems.DataAnalysis;
     33using HeuristicLab.Problems.DataAnalysis.Symbolic;
     34using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
    3235
    3336namespace HeuristicLab.Algorithms.DataAnalysis {
     
    210213    }
    211214
     215    /// <summary>
     216    /// Transforms the tree model to a symbolic regression solution
     217    /// </summary>
     218    /// <param name="problemData"></param>
     219    /// <returns>A new symbolic regression solution which matches the tree model</returns>
     220    public ISymbolicRegressionSolution CreateSymbolicRegressionSolution(IRegressionProblemData problemData) {
     221      var rootSy = new ProgramRootSymbol();
     222      var startSy = new StartSymbol();
     223      var varCondSy = new VariableCondition() { IgnoreSlope = true };
     224      var constSy = new Constant();
     225
     226      var startNode = startSy.CreateTreeNode();
     227      startNode.AddSubtree(CreateSymbolicRegressionTreeRecursive(tree, 0, varCondSy, constSy));
     228      var rootNode = rootSy.CreateTreeNode();
     229      rootNode.AddSubtree(startNode);
     230      var model = new SymbolicRegressionModel(TargetVariable, new SymbolicExpressionTree(rootNode), new SymbolicDataAnalysisExpressionTreeLinearInterpreter());
     231      return model.CreateRegressionSolution(problemData);
     232    }
     233
     234    private ISymbolicExpressionTreeNode CreateSymbolicRegressionTreeRecursive(TreeNode[] treeNodes, int nodeIdx, VariableCondition varCondSy, Constant constSy) {
     235      var curNode = treeNodes[nodeIdx];
     236      if (curNode.VarName == TreeNode.NO_VARIABLE) {
     237        var node = (ConstantTreeNode)constSy.CreateTreeNode();
     238        node.Value = curNode.Val;
     239        return node;
     240      } else {
     241        var node = (VariableConditionTreeNode)varCondSy.CreateTreeNode();
     242        node.VariableName = curNode.VarName;
     243        node.Threshold = curNode.Val;
     244
     245        var left = CreateSymbolicRegressionTreeRecursive(treeNodes, curNode.LeftIdx, varCondSy, constSy);
     246        var right = CreateSymbolicRegressionTreeRecursive(treeNodes, curNode.RightIdx, varCondSy, constSy);
     247        node.AddSubtree(left);
     248        node.AddSubtree(right);
     249        return node;
     250      }
     251    }
     252
     253
    212254    private string TreeToString(int idx, string part) {
    213255      var n = tree[idx];
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