public IFuzzySystem UniversalMethod(IFuzzySystem FSystem, ILearnAlgorithmConf conf)
{
init(FSystem, conf);
for (int m = 0; m < max_Features; m++)
{
for (int i = 0; i < FSystem.CountFeatures; i++)
{
if (BestSolute[i] == true)
{
continue;
}
test.Add(BestSolute.Clone() as bool[]);
test[test.Count - 1][i] = true;
FSystem.AcceptedFeatures = test[test.Count - 1];
Errors.Add(FSystem.ErrorLearnSamples(FSystem.AbstractRulesBase()[0]));
}
int best = Errors.IndexOf(Errors.Min());
BestSolute = test[best].Clone() as bool[];
FSystem.AcceptedFeatures = BestSolute;
Storage.Add(new FeatureSelectionModel(FSystem, BestSolute));
test.Clear();
Errors.Clear();
}
Storage = FeatureSelectionModel.Distinct(Storage);
FeatureSelectionModel.Sort(Storage, SortWay);
return(FSystem);
}
public void newclass()
{
for (int q = 0; q < MCount; q++)
{
if (test[q].Count(x => x == true) == 0)
{
test[q][rand.Next(BestSolute.Count())] = true;
}
;
theFuzzySystem.AcceptedFeatures = test[q];
Errors[q] = theFuzzySystem.ErrorLearnSamples(theFuzzySystem.AbstractRulesBase()[0]);
if (Errors[q] < Ebest)
{
Ebest = Errors[q];
BestSolute = test[q].Clone() as bool[];
// Best_remebed = rules;
Console.WriteLine("Найдена частица с ошибкой E=" + Errors[q]);
Storage.Add(new FeatureSelectionModel(theFuzzySystem, BestSolute));
}
int true_count = test[q].Count(x => x == true);
if ((true_count <= open_Features) && (Errors[q] != Ebest) && (Errors[q] < Ebest1))
{
GoodSolute = test[q].Clone() as bool[];
Storage.Add(new FeatureSelectionModel(theFuzzySystem, GoodSolute));
Console.WriteLine("Найдена дубль-частица с ошибкой E=" + Errors[q]);
}
Console.WriteLine(Errors[q]);
}
}
public FeatureSelectionModel(IFuzzySystem Fsystem, bool[] FeaturesSource)
{
bool[] temp = Fsystem.AcceptedFeatures;
Features = FeaturesSource;
Fsystem.AcceptedFeatures = Features;
Error = Fsystem.ErrorLearnSamples(Fsystem.AbstractRulesBase()[0]);
ErrorTest = Fsystem.ErrorTestSamples(Fsystem.AbstractRulesBase()[0]);
Fsystem.AcceptedFeatures = temp;
if (Fsystem is PCFuzzySystem)
{
Accuracy = 100.0 - Error;
AccuracyTest = 100.0 - ErrorTest;
}
else
{
Error = Fsystem.RMSEtoMSEforLearn(Error);
ErrorTest = Fsystem.RMSEtoMSEforTest(ErrorTest);
}
Info = makeNameFeatures(Fsystem, Features);
}
public IFuzzySystem UniversalMethod(IFuzzySystem FSystem, ILearnAlgorithmConf config)
{
init(FSystem, config);
////////////////////////////////////////////////////////////////////////////////////Первоначальная генерация
for (int u = 0; u < MCount; u++)
{
///Создаем частицу
for (int i = 0; i < max_Features; i++)
{
if (rand.NextDouble() > 0.5)
{
Solute[i] = true;
}
else
{
Solute[i] = false;
}
}
///Проверяем, есть ли признаки. Если частица пуста, рандомный признак становится единицей
if (Solute.Count(x => x == true) == 0)
{
BestSolute[rand.Next(BestSolute.Count())] = true;
}
;
//Заносим частицу в популяцию
test.Add(Solute.Clone() as bool[]);
//Заносим признаки в классификатор
FSystem.AcceptedFeatures = test[test.Count - 1];
Errors.Add(FSystem.ErrorLearnSamples(FSystem.AbstractRulesBase()[0]));
if (Errors[u] < Ebest)
{
Ebest = Errors[u];
BestSolute = test[u].Clone() as bool[];
Console.WriteLine("Найдена частица с ошибкой E=" + Errors[u]);
Storage.Add(new FeatureSelectionModel(FSystem, BestSolute));
}
Console.WriteLine(Errors[u]);
}
/////////////////////////////////////////// Сгенерировали первоначальные частицы, ура!
algoritm();
Storage = FeatureSelectionModel.Distinct(Storage);
FeatureSelectionModel.Sort(Storage, SortWay);
FSystem.AcceptedFeatures = BestSolute;
return(FSystem);
}
private void make_Log(Log_line EventCall, IFuzzySystem FS = null, string name_Alg = "", DateTime TimerValue = new DateTime(), TimeSpan TimerSpan = new TimeSpan())
{
switch (EventCall)
{
case Log_line.Start:
{
LOG += Environment.NewLine + "(" + TimerValue.ToString() + ")" + " Начало построения системы" + Environment.NewLine;
break;
}
case Log_line.StartGenerate:
{
LOG += "(" + TimerValue.ToString() + ")" + " Начата генерация системы { " + FS.LearnSamplesSet.FileName + " ; " + FS.TestSamplesSet.FileName + " }" + Environment.NewLine;
break;
}
case Log_line.StartOptimaze:
{
LOG += "(" + DateTime.Now.ToString() + ")" + " Начата оптимизация системы" + Environment.NewLine;
break;
}
case Log_line.PreGenerate_log:
{
LOG += "(" + DateTime.Now.ToString() + ")" + " Генерация алгоритмом " + name_Alg.ToString() + Environment.NewLine;
break;
}
case Log_line.PostGenerate_log:
{
LOG += "(" + DateTime.Now.ToString() + ")" + " Сгенерирована система сложностью " + FS.ValueComplexity(FS.AbstractRulesBase()[0]).ToString() + Environment.NewLine + " Количество правил " + FS.ValueRuleCount(FS.AbstractRulesBase()[0]).ToString() + Environment.NewLine + showErrorInfo(FS) + "";
LOG += "Использован " + name_Alg.ToString() + Environment.NewLine;
break;
}
case Log_line.PreOptimaze_log:
{
LOG += "(" + DateTime.Now.ToString() + ")" + " Оптимизация алгоритмом " + name_Alg.ToString() + Environment.NewLine;
break;
}
case Log_line.PostOptimaze_log:
{
LOG += "(" + DateTime.Now.ToString() + ")" + " оптимизированная система сложностью " + FS.ValueComplexity(FS.AbstractRulesBase()[0]).ToString() + Environment.NewLine + " Количество правил " + FS.ValueRuleCount(FS.AbstractRulesBase()[0]).ToString() + Environment.NewLine + showErrorInfo(FS) + "";
LOG += "Использован " + name_Alg.ToString() + Environment.NewLine;
break;
}
case Log_line.EndCircle:
{
LOG += "(" + DateTime.Now.ToString() + ")" + " Время построения системы" + TimerSpan.TotalSeconds.ToString() + Environment.NewLine; break;
}
case Log_line.End:
{
LOG += "(" + DateTime.Now.ToString() + ")" + " Время построения всех систем" + TimerSpan.TotalSeconds.ToString() + Environment.NewLine; break;
}
default: { LOG += "Не верный вызов" + Environment.NewLine; break; }
}
}