#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; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding; using HeuristicLab.Operators; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; using HeuristicLab.Problems.DataAnalysis.Evaluators; using HeuristicLab.Problems.DataAnalysis.Symbolic; 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] [Obsolete("This class should not be used anymore because of performance reasons and will therefore not be updated.")] 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 } } }