- Timestamp:
- 07/23/17 00:52:14 (7 years ago)
- Location:
- branches/Async
- Files:
-
- 4 edited
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branches/Async
- Property svn:mergeinfo changed
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branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic
- Property svn:mergeinfo changed
/trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic (added) merged: 13395,13397,13616,13916,13921,13933,13941
- Property svn:mergeinfo changed
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branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Evaluators/SymbolicDataAnalysisEvaluator.cs
r12012 r15280 93 93 public SymbolicDataAnalysisEvaluator() 94 94 : base() { 95 Parameters.Add(new ValueLookupParameter<IRandom>(RandomParameterName, "The random generator to use.") );96 Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicDataAnalysisTreeInterpreterParameterName, "The interpreter that should be used to calculate the output values of the symbolic data analysis tree.") );97 Parameters.Add(new LookupParameter<ISymbolicExpressionTree>(SymbolicExpressionTreeParameterName, "The symbolic data analysis solution encoded as a symbolic expression tree.") );98 Parameters.Add(new ValueLookupParameter<T>(ProblemDataParameterName, "The problem data on which the symbolic data analysis solution should be evaluated.") );99 Parameters.Add(new ValueLookupParameter<IntRange>(EvaluationPartitionParameterName, "The start index of the dataset partition on which the symbolic data analysis solution should be evaluated.") );100 Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The upper and lower limit that should be used as cut off value for the output values of symbolic data analysis trees.") );101 Parameters.Add(new ValueLookupParameter<PercentValue>(RelativeNumberOfEvaluatedSamplesParameterName, "The relative number of samples of the dataset partition, which should be randomly chosen for evaluation between the start and end index.") );102 Parameters.Add(new LookupParameter<BoolValue>(ApplyLinearScalingParameterName, "Flag that indicates if the individual should be linearly scaled before evaluating.") );103 Parameters.Add(new ValueLookupParameter<StringValue>(ValidRowIndicatorParameterName, "An indicator variable in the data set that specifies which rows should be evaluated (those for which the indicator <> 0) (optional).") );95 Parameters.Add(new ValueLookupParameter<IRandom>(RandomParameterName, "The random generator to use.") { Hidden = true }); 96 Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicDataAnalysisTreeInterpreterParameterName, "The interpreter that should be used to calculate the output values of the symbolic data analysis tree.") { Hidden = true }); 97 Parameters.Add(new LookupParameter<ISymbolicExpressionTree>(SymbolicExpressionTreeParameterName, "The symbolic data analysis solution encoded as a symbolic expression tree.") { Hidden = true }); 98 Parameters.Add(new ValueLookupParameter<T>(ProblemDataParameterName, "The problem data on which the symbolic data analysis solution should be evaluated.") { Hidden = true }); 99 Parameters.Add(new ValueLookupParameter<IntRange>(EvaluationPartitionParameterName, "The start index of the dataset partition on which the symbolic data analysis solution should be evaluated.") { Hidden = true }); 100 Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The upper and lower limit that should be used as cut off value for the output values of symbolic data analysis trees.") { Hidden = true }); 101 Parameters.Add(new ValueLookupParameter<PercentValue>(RelativeNumberOfEvaluatedSamplesParameterName, "The relative number of samples of the dataset partition, which should be randomly chosen for evaluation between the start and end index.") { Hidden = true }); 102 Parameters.Add(new LookupParameter<BoolValue>(ApplyLinearScalingParameterName, "Flag that indicates if the individual should be linearly scaled before evaluating.") { Hidden = true }); 103 Parameters.Add(new ValueLookupParameter<StringValue>(ValidRowIndicatorParameterName, "An indicator variable in the data set that specifies which rows should be evaluated (those for which the indicator <> 0) (optional).") { Hidden = true }); 104 104 } 105 105 -
branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Evaluators/SymbolicDataAnalysisMultiObjectiveEvaluator.cs
r12012 r15280 24 24 using HeuristicLab.Core; 25 25 using HeuristicLab.Data; 26 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding; 26 27 using HeuristicLab.Parameters; 27 28 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; 28 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;29 29 30 30 namespace HeuristicLab.Problems.DataAnalysis.Symbolic { 31 [StorableClass] 31 32 public abstract class SymbolicDataAnalysisMultiObjectiveEvaluator<T> : SymbolicDataAnalysisEvaluator<T>, ISymbolicDataAnalysisMultiObjectiveEvaluator<T> 32 33 where T : class, IDataAnalysisProblemData {
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