public bool Classify(List <IdNumber> idNumbersList, ClassProbabilty classProbabilty, List <ProbabilityOfFeatureValue> probabilityOfFeatureValues)
{
var pP = 1.00;
var pN = 1.00;
var pX = 1.00;
foreach (var item in idNumbersList)
{
var result = probabilityOfFeatureValues.Where(p => p.FeatureId == item.Id && p.PropertyValue.Equals(item.Number)).FirstOrDefault();
if (result != null)
{
pP *= result.PositiveProbability;
pN *= result.NegativeProbability;
pX *= result.AllProbability;
}
}
var pPResult = pP / pX;
var pNResult = pN / pX;
if (pPResult > pNResult)
{
return(true);
}
else
{
return(false);
}
}
public List <bool> ClassifyAllTable(List <List <double> > dataSet, ClassProbabilty classProbabilty, List <ProbabilityOfFeatureValue> probabilityOfFeatureValues)
{
List <bool> classifyResult = new List <bool>();
for (int i = 0; i < dataSet[0].Count; i++)
{
List <IdNumber> idNumbersList = new List <IdNumber>();
for (int j = 0; j < dataSet.Count; j++)
{
idNumbersList.Add(new IdNumber(j, dataSet[j][i]));
}
classifyResult.Add(Classify(idNumbersList, classProbabilty, probabilityOfFeatureValues));
Console.WriteLine($"numer klasyfikacji: {i}");
}
return(classifyResult);
}
public List <bool> ClassifyTableWithSelectedFeatures(List <List <double> > dataSet, ClassProbabilty classProbabilty, List <ProbabilityOfFeatureValue> probabilityOfFeatureValues, List <IdNumber> selectedFeaturesWithCorrelation)
{
List <bool> classifyResult = new List <bool>();
for (int i = 0; i < dataSet[0].Count; i++)
{
List <IdNumber> idNumbersList = new List <IdNumber>();
foreach (var item in selectedFeaturesWithCorrelation)
{
idNumbersList.Add(new IdNumber(item.Id, dataSet[item.Id][i]));
}
classifyResult.Add(Classify(idNumbersList, classProbabilty, probabilityOfFeatureValues));
Console.WriteLine($"numer klasyfikacji: {i}");
}
return(classifyResult);
}