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Ignore:
Timestamp:
11/15/16 20:23:12 (8 years ago)
Author:
gkronber
Message:

#2697:

  • extended converter for linear models to support lagged variables and changed AR(k) to use this method
File:
1 edited

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  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/TimeSeries/AutoregressiveModeling.cs

    r14185 r14391  
    114114      alglib.lrunpack(lm, out coefficients, out nFeatures);
    115115
    116 
    117       ISymbolicExpressionTree tree = new SymbolicExpressionTree(new ProgramRootSymbol().CreateTreeNode());
    118       ISymbolicExpressionTreeNode startNode = new StartSymbol().CreateTreeNode();
    119       tree.Root.AddSubtree(startNode);
    120       ISymbolicExpressionTreeNode addition = new Addition().CreateTreeNode();
    121       startNode.AddSubtree(addition);
    122 
    123       for (int i = 0; i < timeOffset; i++) {
    124         LaggedVariableTreeNode node = (LaggedVariableTreeNode)new LaggedVariable().CreateTreeNode();
    125         node.VariableName = targetVariable;
    126         node.Weight = coefficients[i];
    127         node.Lag = (i + 1) * -1;
    128         addition.AddSubtree(node);
    129       }
    130 
    131       ConstantTreeNode cNode = (ConstantTreeNode)new Constant().CreateTreeNode();
    132       cNode.Value = coefficients[coefficients.Length - 1];
    133       addition.AddSubtree(cNode);
     116      var tree = LinearModelToTreeConverter.CreateTree(
     117        variableNames: Enumerable.Repeat(problemData.TargetVariable, nFeatures).ToArray(),
     118        lags: Enumerable.Range(0, timeOffset).Select(i => (i + 1) * -1).ToArray(),
     119        coefficients: coefficients.Take(nFeatures).ToArray(),
     120        @const: coefficients[nFeatures]
     121        );
    134122
    135123      var interpreter = new SymbolicTimeSeriesPrognosisExpressionTreeInterpreter(problemData.TargetVariable);
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