protected SymbolicDataAnalysisProblem(T problemData, U evaluator, V solutionCreator)
: base(evaluator, solutionCreator)
{
Parameters.Add(new ValueParameter <T>(ProblemDataParameterName, ProblemDataParameterDescription, problemData));
Parameters.Add(new ValueParameter <ISymbolicDataAnalysisGrammar>(SymbolicExpressionTreeGrammarParameterName, SymbolicExpressionTreeGrammarParameterDescription));
Parameters.Add(new ValueParameter <ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicExpressionTreeInterpreterParameterName, SymoblicExpressionTreeInterpreterParameterDescription));
Parameters.Add(new FixedValueParameter <IntValue>(MaximumSymbolicExpressionTreeDepthParameterName, MaximumSymbolicExpressionTreeDepthParameterDescription));
Parameters.Add(new FixedValueParameter <IntValue>(MaximumSymbolicExpressionTreeLengthParameterName, MaximumSymbolicExpressionTreeLengthParameterDescription));
Parameters.Add(new FixedValueParameter <IntValue>(MaximumFunctionDefinitionsParameterName, MaximumFunctionDefinitionsParameterDescription));
Parameters.Add(new FixedValueParameter <IntValue>(MaximumFunctionArgumentsParameterName, MaximumFunctionArgumentsParameterDescription));
Parameters.Add(new FixedValueParameter <IntRange>(FitnessCalculationPartitionParameterName, FitnessCalculationPartitionParameterDescription));
Parameters.Add(new FixedValueParameter <IntRange>(ValidationPartitionParameterName, ValidationPartitionParameterDescription));
Parameters.Add(new FixedValueParameter <PercentValue>(RelativeNumberOfEvaluatedSamplesParameterName, RelativeNumberOfEvaluatedSamplesParameterDescription, new PercentValue(1)));
Parameters.Add(new FixedValueParameter <BoolValue>(ApplyLinearScalingParameterName, ApplyLinearScalingParameterDescription, new BoolValue(false)));
SymbolicExpressionTreeInterpreterParameter.Hidden = true;
MaximumFunctionArgumentsParameter.Hidden = true;
MaximumFunctionDefinitionsParameter.Hidden = true;
ApplyLinearScalingParameter.Hidden = true;
SymbolicExpressionTreeGrammar = new TypeCoherentExpressionGrammar();
SymbolicExpressionTreeInterpreter = new SymbolicDataAnalysisExpressionTreeLinearInterpreter();
FitnessCalculationPartition.Start = ProblemData.TrainingPartition.Start;
FitnessCalculationPartition.End = ProblemData.TrainingPartition.End;
InitializeOperators();
UpdateGrammar();
RegisterEventHandlers();
}
private SymbolicDataAnalysisExpressionTreeLinearInterpreter(SymbolicDataAnalysisExpressionTreeLinearInterpreter original, Cloner cloner)
: base(original, cloner)
{
interpreter = cloner.Clone(original.interpreter);
}
private static ISymbolicRegressionSolution CreateSymbolicSolution(List<IRegressionModel> models, double nu, IRegressionProblemData problemData) {
var symbModels = models.OfType<ISymbolicRegressionModel>();
var lowerLimit = symbModels.Min(m => m.LowerEstimationLimit);
var upperLimit = symbModels.Max(m => m.UpperEstimationLimit);
var interpreter = new SymbolicDataAnalysisExpressionTreeLinearInterpreter();
var progRootNode = new ProgramRootSymbol().CreateTreeNode();
var startNode = new StartSymbol().CreateTreeNode();
var addNode = new Addition().CreateTreeNode();
var mulNode = new Multiplication().CreateTreeNode();
var scaleNode = (ConstantTreeNode)new Constant().CreateTreeNode(); // all models are scaled using the same nu
scaleNode.Value = nu;
foreach (var m in symbModels) {
var relevantPart = m.SymbolicExpressionTree.Root.GetSubtree(0).GetSubtree(0); // skip root and start
addNode.AddSubtree((ISymbolicExpressionTreeNode)relevantPart.Clone());
}
mulNode.AddSubtree(addNode);
mulNode.AddSubtree(scaleNode);
startNode.AddSubtree(mulNode);
progRootNode.AddSubtree(startNode);
var t = new SymbolicExpressionTree(progRootNode);
var combinedModel = new SymbolicRegressionModel(problemData.TargetVariable, t, interpreter, lowerLimit, upperLimit);
var sol = new SymbolicRegressionSolution(combinedModel, problemData);
return sol;
}
private SymbolicDataAnalysisExpressionTreeLinearInterpreter(SymbolicDataAnalysisExpressionTreeLinearInterpreter original, Cloner cloner)
: base(original, cloner) {
interpreter = cloner.Clone(original.interpreter);
}