#region License Information
/* HeuristicLab
* Copyright (C) 2002-2019 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.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HEAL.Attic;
namespace HeuristicLab.Problems.DataAnalysis {
///
/// Represents a classification solution that uses a discriminant function and classification thresholds.
///
[StorableType("A3480DF9-49E7-4329-AD23-57B4441033C1")]
[Item("DiscriminantFunctionClassificationSolution", "Represents a classification solution that uses a discriminant function and classification thresholds.")]
public class DiscriminantFunctionClassificationSolution : DiscriminantFunctionClassificationSolutionBase {
protected readonly Dictionary valueEvaluationCache;
protected readonly Dictionary classValueEvaluationCache;
[StorableConstructor]
protected DiscriminantFunctionClassificationSolution(StorableConstructorFlag _) : base(_) {
valueEvaluationCache = new Dictionary();
classValueEvaluationCache = new Dictionary();
}
protected DiscriminantFunctionClassificationSolution(DiscriminantFunctionClassificationSolution original, Cloner cloner)
: base(original, cloner) {
valueEvaluationCache = new Dictionary(original.valueEvaluationCache);
classValueEvaluationCache = new Dictionary(original.classValueEvaluationCache);
}
public DiscriminantFunctionClassificationSolution(IDiscriminantFunctionClassificationModel model, IClassificationProblemData problemData)
: base(model, problemData) {
valueEvaluationCache = new Dictionary();
classValueEvaluationCache = new Dictionary();
CalculateRegressionResults();
CalculateClassificationResults();
}
public override IDeepCloneable Clone(Cloner cloner) {
return new DiscriminantFunctionClassificationSolution(this, cloner);
}
public override IEnumerable EstimatedClassValues {
get { return GetEstimatedClassValues(Enumerable.Range(0, ProblemData.Dataset.Rows)); }
}
public override IEnumerable EstimatedTrainingClassValues {
get { return GetEstimatedClassValues(ProblemData.TrainingIndices); }
}
public override IEnumerable EstimatedTestClassValues {
get { return GetEstimatedClassValues(ProblemData.TestIndices); }
}
public override IEnumerable GetEstimatedClassValues(IEnumerable rows) {
var rowsToEvaluate = rows.Except(classValueEvaluationCache.Keys);
var rowsEnumerator = rowsToEvaluate.GetEnumerator();
var valuesEnumerator = Model.GetEstimatedClassValues(ProblemData.Dataset, rowsToEvaluate).GetEnumerator();
while (rowsEnumerator.MoveNext() & valuesEnumerator.MoveNext()) {
classValueEvaluationCache.Add(rowsEnumerator.Current, valuesEnumerator.Current);
}
return rows.Select(row => classValueEvaluationCache[row]);
}
public override IEnumerable EstimatedValues {
get { return GetEstimatedValues(Enumerable.Range(0, ProblemData.Dataset.Rows)); }
}
public override IEnumerable EstimatedTrainingValues {
get { return GetEstimatedValues(ProblemData.TrainingIndices); }
}
public override IEnumerable EstimatedTestValues {
get { return GetEstimatedValues(ProblemData.TestIndices); }
}
public override IEnumerable GetEstimatedValues(IEnumerable rows) {
var rowsToEvaluate = rows.Except(valueEvaluationCache.Keys);
var rowsEnumerator = rowsToEvaluate.GetEnumerator();
var valuesEnumerator = Model.GetEstimatedValues(ProblemData.Dataset, rowsToEvaluate).GetEnumerator();
while (rowsEnumerator.MoveNext() & valuesEnumerator.MoveNext()) {
valueEvaluationCache.Add(rowsEnumerator.Current, valuesEnumerator.Current);
}
return rows.Select(row => valueEvaluationCache[row]);
}
protected override void OnModelChanged() {
valueEvaluationCache.Clear();
classValueEvaluationCache.Clear();
base.OnModelChanged();
}
protected override void OnModelThresholdsChanged(System.EventArgs e) {
classValueEvaluationCache.Clear();
base.OnModelThresholdsChanged(e);
}
protected override void OnProblemDataChanged() {
valueEvaluationCache.Clear();
classValueEvaluationCache.Clear();
base.OnProblemDataChanged();
}
}
}