#region License Information
/* HeuristicLab
* Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Problems.DataAnalysis.Regression.Symbolic;
using HeuristicLab.Problems.DataAnalysis.Symbolic;
using System.Collections.Generic;
using HeuristicLab.Problems.DataAnalysis.Symbolic.Symbols;
using HeuristicLab.Problems.DataAnalysis;
using HeuristicLab.Analysis;
using HeuristicLab.Problems.DataAnalysis.Evaluators;
namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Analyzers {
///
/// "An operator to calculate the quality values of a symbolic regression solution symbolic expression tree encoding."
///
[Item("SymbolicRegressionModelQualityCalculator", "An operator to calculate the quality values of a symbolic regression solution symbolic expression tree encoding.")]
[StorableClass]
public sealed class SymbolicRegressionModelQualityCalculator : AlgorithmOperator {
private const string SymbolicExpressionTreeInterpreterParameterName = "SymbolicExpressionTreeInterpreter";
private const string SymbolicExpressionTreeParameterName = "SymbolicExpressionTree";
private const string ProblemDataParameterName = "ProblemData";
private const string ValuesParameterName = "Values";
private const string RSQuaredQualityParameterName = "R-squared";
private const string MeanSquaredErrorQualityParameterName = "Mean Squared Error";
private const string RelativeErrorQualityParameterName = "Relative Error";
private const string SamplesStartParameterName = "SamplesStart";
private const string SamplesEndParameterName = "SamplesEnd";
private const string UpperEstimationLimitParameterName = "UpperEstimationLimit";
private const string LowerEstimationLimitParameterName = "LowerEstimationLimit";
#region parameter properties
public ILookupParameter SymbolicExpressionTreeParameter {
get { return (ILookupParameter)Parameters[SymbolicExpressionTreeParameterName]; }
}
public IValueLookupParameter SymbolicExpressionTreeInterpreterParameter {
get { return (IValueLookupParameter)Parameters[SymbolicExpressionTreeInterpreterParameterName]; }
}
public IValueLookupParameter ProblemDataParameter {
get { return (IValueLookupParameter)Parameters[ProblemDataParameterName]; }
}
public IValueLookupParameter SamplesStartParameter {
get { return (IValueLookupParameter)Parameters[SamplesStartParameterName]; }
}
public IValueLookupParameter SamplesEndParameter {
get { return (IValueLookupParameter)Parameters[SamplesEndParameterName]; }
}
public IValueLookupParameter UpperEstimationLimitParameter {
get { return (IValueLookupParameter)Parameters[UpperEstimationLimitParameterName]; }
}
public IValueLookupParameter LowerEstimationLimitParameter {
get { return (IValueLookupParameter)Parameters[LowerEstimationLimitParameterName]; }
}
public ILookupParameter RSquaredQualityParameter {
get { return (ILookupParameter)Parameters[RSQuaredQualityParameterName]; }
}
public ILookupParameter AverageRelativeErrorQualityParameter {
get { return (ILookupParameter)Parameters[RelativeErrorQualityParameterName]; }
}
public ILookupParameter MeanSquaredErrorQualityParameter {
get { return (ILookupParameter)Parameters[MeanSquaredErrorQualityParameterName]; }
}
#endregion
public SymbolicRegressionModelQualityCalculator()
: base() {
Parameters.Add(new LookupParameter(SymbolicExpressionTreeParameterName, "The symbolic expression tree to analyze."));
Parameters.Add(new ValueLookupParameter(SymbolicExpressionTreeInterpreterParameterName, "The interpreter that should be used to calculate the output values of the symbolic expression tree."));
Parameters.Add(new ValueLookupParameter(ProblemDataParameterName, "The problem data containing the input varaibles for the symbolic regression problem."));
Parameters.Add(new ValueLookupParameter(SamplesStartParameterName, "The first index of the data set partition on which the model quality values should be calculated."));
Parameters.Add(new ValueLookupParameter(SamplesEndParameterName, "The first index of the data set partition on which the model quality values should be calculated."));
Parameters.Add(new ValueLookupParameter(UpperEstimationLimitParameterName, "The upper limit that should be used as cut off value for the output values of symbolic expression trees."));
Parameters.Add(new ValueLookupParameter(LowerEstimationLimitParameterName, "The lower limit that should be used as cut off value for the output values of symbolic expression trees."));
Parameters.Add(new ValueParameter(ValuesParameterName, "The matrix of original target values and estimated values of the model."));
Parameters.Add(new ValueLookupParameter(MeanSquaredErrorQualityParameterName, "The mean squared error value of the output of the model."));
Parameters.Add(new ValueLookupParameter(RSQuaredQualityParameterName, "The Rē correlation coefficient of the output of the model and the original target values."));
Parameters.Add(new ValueLookupParameter(RelativeErrorQualityParameterName, "The average relative percentage error of the output of the model."));
#region operator initialization
SimpleSymbolicRegressionEvaluator simpleEvaluator = new SimpleSymbolicRegressionEvaluator();
SimpleRSquaredEvaluator simpleR2Evalator = new SimpleRSquaredEvaluator();
SimpleMeanAbsolutePercentageErrorEvaluator simpleRelErrorEvaluator = new SimpleMeanAbsolutePercentageErrorEvaluator();
SimpleMSEEvaluator simpleMseEvaluator = new SimpleMSEEvaluator();
Assigner clearValues = new Assigner();
#endregion
#region parameter wiring
simpleEvaluator.SymbolicExpressionTreeParameter.ActualName = SymbolicExpressionTreeParameter.Name;
simpleEvaluator.RegressionProblemDataParameter.ActualName = ProblemDataParameter.Name;
simpleEvaluator.SamplesStartParameter.ActualName = SamplesStartParameter.Name;
simpleEvaluator.SamplesEndParameter.ActualName = SamplesEndParameter.Name;
simpleEvaluator.LowerEstimationLimitParameter.ActualName = LowerEstimationLimitParameter.Name;
simpleEvaluator.UpperEstimationLimitParameter.ActualName = UpperEstimationLimitParameter.Name;
simpleEvaluator.SymbolicExpressionTreeInterpreterParameter.ActualName = SymbolicExpressionTreeInterpreterParameter.Name;
simpleEvaluator.ValuesParameter.ActualName = ValuesParameterName;
simpleR2Evalator.ValuesParameter.ActualName = ValuesParameterName;
simpleR2Evalator.RSquaredParameter.ActualName = RSquaredQualityParameter.Name;
simpleMseEvaluator.ValuesParameter.ActualName = ValuesParameterName;
simpleMseEvaluator.MeanSquaredErrorParameter.ActualName = MeanSquaredErrorQualityParameter.Name;
simpleRelErrorEvaluator.ValuesParameter.ActualName = ValuesParameterName;
simpleRelErrorEvaluator.AverageRelativeErrorParameter.ActualName = AverageRelativeErrorQualityParameter.Name;
clearValues.LeftSideParameter.ActualName = ValuesParameterName;
clearValues.RightSideParameter.Value = new DoubleMatrix();
#endregion
#region operator graph
OperatorGraph.InitialOperator = simpleEvaluator;
simpleEvaluator.Successor = simpleR2Evalator;
simpleR2Evalator.Successor = simpleRelErrorEvaluator;
simpleRelErrorEvaluator.Successor = simpleMseEvaluator;
simpleMseEvaluator.Successor = clearValues;
clearValues.Successor = null;
#endregion
}
}
}