private double getInterpreting(PCFuzzySystem Classifier, double allowSquare, double allowBorder)
{
switch (typeInterpreting)
{
case 0: return(Classifier.getNormalIndex(allowBorder, allowSquare));
case 1: return(Classifier.getIndexReal(allowBorder, allowBorder));
default: return(Classifier.getNormalIndex(allowBorder, allowBorder));
}
}
private void addClassifierValue(PCFuzzySystem Classifier)
{
double Value = Classifier.ClassifyLearnSamples(Classifier.RulesDatabaseSet[0]);
ValueLGoodsPercent.Add(Value);
ValueLGoodsError.Add(100 - Value);
Value = Classifier.ClassifyTestSamples(Classifier.RulesDatabaseSet[0]);
ValueTGoodsPercent.Add(Value);
ValueTGoodsError.Add(100 - Value);
Value = Classifier.getComplexit();
ValueComplexityFull.Add(Value);
Value = Classifier.getRulesCount();
ValueComplexityRules.Add(Value);
Value = Classifier.getNormalIndex();
ValueInterpretyNominal.Add(Value);
Value = Classifier.getIndexReal();
ValueInterpretyReal.Add(Value);
}
public override void Work()
{
GIBNormal = fuzzy_system.getGIBNormal();
GIBSumStraigth = fuzzy_system.getGIBSumStrait();
GIBSumReverce = fuzzy_system.getGIBSumReverse();
GICNormal = fuzzy_system.getGICNormal();
GICSumReverce = fuzzy_system.getGICSumReverce();
GICSumStraigh = fuzzy_system.getGICSumStraigth();
GISNormal = fuzzy_system.getGISNormal();
GISSumReverce = fuzzy_system.getGISSumReverce();
GISSumStraigth = fuzzy_system.getGISSumStraigt();
LindisNormal = fuzzy_system.getLindisNormal();
LindisSumStraigh = fuzzy_system.getLindisSumStraight();
LindisSumReverce = fuzzy_system.getLindisSumReverse();
NormalIndex = fuzzy_system.getNormalIndex();
SumReverseIndex = fuzzy_system.getIndexSumReverse();
SumsStraigthIndex = fuzzy_system.getIndexSumStraigt();
PCFSUFSWriter.saveToUFS(fuzzy_system, Source);
}
private static void writeAboutEstimates(XmlWriter writer, PCFuzzySystem Classifier)
{
writer.WriteStartElement("Estimates");
if (Classifier.TestSamplesSet != null)
{
writer.WriteAttributeString("Count", XmlConvert.ToString(22));
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Table", Classifier.LearnSamplesSet.FileName);
writer.WriteAttributeString("Type", "PrecisionPercent");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.ClassifyLearnSamples(Classifier.RulesDatabaseSet[0])));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Table", Classifier.LearnSamplesSet.FileName);
writer.WriteAttributeString("Type", "ErrorPercent");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.ErrorLearnSamples(Classifier.RulesDatabaseSet[0])));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Table", Classifier.TestSamplesSet.FileName);
writer.WriteAttributeString("Type", "PrecisionPercent");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.ClassifyTestSamples(Classifier.RulesDatabaseSet[0])));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Table", Classifier.TestSamplesSet.FileName);
writer.WriteAttributeString("Type", "ErrorPercent");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.ErrorTestSamples(Classifier.RulesDatabaseSet[0])));
writer.WriteEndElement();
}
else
{
writer.WriteAttributeString("Count", XmlConvert.ToString(20));
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Table", Classifier.LearnSamplesSet.FileName);
writer.WriteAttributeString("Type", "PrecisionPercent");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.ClassifyLearnSamples(Classifier.RulesDatabaseSet[0])));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Table", Classifier.LearnSamplesSet.FileName);
writer.WriteAttributeString("Type", "ErrorPercent");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.ErrorLearnSamples(Classifier.RulesDatabaseSet[0])));
writer.WriteEndElement();
}
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "GIBNormal");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getGIBNormal()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "GIBSumStraigh");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getGIBSumStrait()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "GIBSumReverse");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getGIBSumReverse()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "GICNormal");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getGICNormal()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "GICSumStraigh");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getGICSumStraigth()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "GICSumReverse");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getGICSumReverce()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "GISNormal");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getGISNormal()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "GISSumStraigh");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getGISSumStraigt()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "GISSumReverce");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getGISSumReverce()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "LindisNormal");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getLindisNormal()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "LindisSumStraigh");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getLindisSumStraight()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "LindisSumReverse");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getLindisSumReverse()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "NormalIndex");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getNormalIndex()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "RealIndex");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getIndexReal()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "SumStraigthIndex");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getIndexSumStraigt()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "SumReverseIndex");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getIndexSumReverse()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "ComplexitIt");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getComplexit()));
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
writer.WriteAttributeString("Type", "CountRules");
writer.WriteAttributeString("Value", XmlConvert.ToString(Classifier.getRulesCount()));
writer.WriteEndElement();
writer.WriteEndElement();
}
