- Timestamp:
- 07/06/17 11:12:18 (7 years ago)
- File:
-
- 1 edited
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stable/HeuristicLab.Algorithms.DataAnalysis/3.4/TimeSeries/AutoregressiveModeling.cs
r15061 r15142 115 115 alglib.lrunpack(lm, out coefficients, out nFeatures); 116 116 117 118 ISymbolicExpressionTree tree = new SymbolicExpressionTree(new ProgramRootSymbol().CreateTreeNode()); 119 ISymbolicExpressionTreeNode startNode = new StartSymbol().CreateTreeNode(); 120 tree.Root.AddSubtree(startNode); 121 ISymbolicExpressionTreeNode addition = new Addition().CreateTreeNode(); 122 startNode.AddSubtree(addition); 123 124 for (int i = 0; i < timeOffset; i++) { 125 LaggedVariableTreeNode node = (LaggedVariableTreeNode)new LaggedVariable().CreateTreeNode(); 126 node.VariableName = targetVariable; 127 node.Weight = coefficients[i]; 128 node.Lag = (i + 1) * -1; 129 addition.AddSubtree(node); 130 } 131 132 ConstantTreeNode cNode = (ConstantTreeNode)new Constant().CreateTreeNode(); 133 cNode.Value = coefficients[coefficients.Length - 1]; 134 addition.AddSubtree(cNode); 117 var tree = LinearModelToTreeConverter.CreateTree( 118 variableNames: Enumerable.Repeat(problemData.TargetVariable, nFeatures).ToArray(), 119 lags: Enumerable.Range(0, timeOffset).Select(i => (i + 1) * -1).ToArray(), 120 coefficients: coefficients.Take(nFeatures).ToArray(), 121 @const: coefficients[nFeatures] 122 ); 135 123 136 124 var interpreter = new SymbolicTimeSeriesPrognosisExpressionTreeInterpreter(problemData.TargetVariable);
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